Database systems design implementation and management 12th edition etextbook pdf

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Contents Part 1: Database Concepts 1 Chapter 1: Database Systems 2 1-1 Why Databases? 3 1-2 Data versus Information 4 1-3 Introducing the Database 6

1-3a Role and Advantages of the DBMS 6 1-3b Types of Databases 8

1-4 Why Database Design is Important 11 1-5 Evolution of File System Data Processing 14

1-5a Manual File Systems 14 1-5b Computerized File Systems 15 1-5c File System Redux: Modern End-User ­Productivity Tools 17

1-6 Problems with File System Data Processing 18 1-6a Structural and Data Dependence 19 1-6b Data Redundancy 20 1-6c Data Anomalies 21

1-7 Database Systems 21

1-7a The Database System Environment 22 1-7b DBMS Functions 24 1-7c Managing the Database System: A Shift in Focus 28

1-8 Preparing for Your Database Professional ­Career 28 Summary 30 • Key Terms 31 • Review Questions 32 • Problems 32

Chapter 2: Data Models 35 2-1 Data Modeling and Data Models 36 2-2 The Importance of Data Models 37 2-3 Data Model Basic Building Blocks 37 2-4 Business Rules 39

2-4a Discovering Business Rules 39 2-4b Translating Business Rules into Data Model Components 40 2-4c Naming Conventions 41

2-5 The Evolution of Data Models 41

2-5a Hierarchical and Network Models 41 2-5b The Relational Model 43 2-5c The Entity Relationship Model 45 2-5d The Object-Oriented (OO) Model 48 2-5e Object/Relational and XML 49 2-5f Emerging Data Models: Big Data and NoSQL 50 2-5g Data Models: A Summary 56

2-6 Degrees of Data Abstraction 57 2-6a The External Model 60 2-6b The Conceptual Model 61 2-6c The Internal Model 62 2-6d The Physical Model 63

Summary 64 • Key Terms 65 • Review Questions 65 • Problems 66

Part 2: Design Concepts 71 Chapter 3: The Relational Database Model 72 3-1 A Logical View of Data 73

3-1a Tables and Their Characteristics 73

vi Contents

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3-2 Keys 76

3-2a Dependencies 76 3-2b Types of Keys 77

3-3 Integrity Rules 80 3-4 Relational Algebra 82

3-4a Formal Definitions and Terminology 82 3-4b Relational Set Operators 83

3-5 The Data Dictionary and the System Catalog 91 3-6 Relationships within the Relational Database 93 3-6a The 1:M Relationship 93 3-6b The 1:1 Relationship 95 3-6c The M:N Relationship 97

3-7 Data Redundancy Revisited 101 3-8 Indexes 103 3-9 Codd’s Relational Database Rules 104 Summary 106 • Key Terms 107 • Review Questions 107 • Problems 110

Chapter 4: Entity Relationship (ER) Modeling 117 4-1 The Entity Relationship Model (ERM) 118 4-1a Entities 118 4-1b Attributes 118 4-1c Relationships 124 4-1d Connectivity and Cardinality 125 4-1e Existence Dependence 126 4-1f Relationship Strength 126 4-1g Weak Entities 129 4-1h Relationship Participation 131 4-1i Relationship Degree 134 4-1j Recursive Relationships 136 4-1k Associative (Composite) Entities 138

4-2 Developing an ER Diagram 140 4-3 Database Design Challenges: Conflicting Goals 147 Summary 152 • Key Terms 153 • Review Questions 153 • Problems 156 • Cases 161

Chapter 5: Advanced Data Modeling 169 5-1 The Extended Entity Relationship Model 170 5-1a Entity Supertypes and Subtypes 170 5-1b Specialization Hierarchy 171 5-1c Inheritance 172 5-1d Subtype Discriminator 174 5-1e Disjoint and Overlapping Constraints 174 5-1f Completeness Constraint 175 5-1g Specialization and Generalization 176

5-2 Entity Clustering 176 5-3 Entity Integrity: Selecting Primary Keys 177

5-3a Natural Keys and Primary Keys 178 5-3b Primary Key Guidelines 178 5-3c When To Use Composite Primary Keys 178 5-3d When To Use Surrogate Primary Keys 180

5-4 Design Cases: Learning Flexible Database Design 182

5-4a Design Case 1: Implementing 1:1 Relationships 182 5-4b Design Case 2: Maintaining History of Time-Variant Data 183 5-4c Design Case 3: Fan Traps 186 5-4d Design Case 4: Redundant Relationships 187

Summary 188 • Key Terms 189 • Review Questions 189 • Problems 190 • Cases 192

Chapter 6: Normalization of Database Tables 201 6-1 Database Tables and Normalization 202 6-2 The Need For Normalization 202 6-3 The Normalization Process 206

6-3a Conversion To First Normal Form 208 6-3b Conversion To Second Normal Form 211 6-3c Conversion To Third Normal Form 213

Contents vii

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6-4 Improving the Design 215 6-5 Surrogate Key Considerations 219 6-6 Higher-Level Normal Forms 220

6-6a The Boyce-Codd Normal Form 221 6-6b Fourth Normal Form (4NF) 224

6-7 Normalization and Database Design 226 6-8 Denormalization 229 6-9 Data-Modeling Checklist 232 Summary 234 • Key Terms 235 • Review Questions 235 • Problems 237

Part 3: Advanced Design and Implementation 245 Chapter 7: Introduction to Structured Query Language (SQL) 246 7-1 Introduction to SQL 247 7-2 Data Definition Commands 249

7-2a The Database Model 249 7-2b Creating The Database 251 7-2c The Database Schema 251 7-2d Data Types 252 7-2e Creating Table Structures 255 7-2f SQL Constraints 259 7-2g SQL Indexes 263

7-3 Data Manipulation Commands 264

7-3a Adding Table Rows 264 7-3b Saving Table Changes 266 7-3c Listing Table Rows 266 7-3d Updating Table Rows 268 7-3e Restoring Table Contents 269 7-3f Deleting Table Rows 269 7-3g Inserting Table Rows with a Select Subquery 270

7.4 SELECT Queries 271

7-4a Selecting Rows with Conditional Restrictions 271 7-4b Arithmetic Operators: The Rule of Precedence 276 7-4c Logical Operators: AND, OR, and NOT 277 7-4d Special Operators 279

7-5 Additional Data Definition Commands 283

7-5a Changing a Column’s Data Type 284 7-5b Changing a Column’s Data Characteristics 284 7-5c Adding a Column 284 7-5d Dropping a Column 285 7-5e Advanced Data Updates 285 7-5f Copying Parts of Tables 287 7-5g Adding Primary and Foreign Key Designations 289 7-5h Deleting a Table from the Database 290

7-6 Additional SELECT Query Keywords 290 7-6a Ordering a Listing 290 7-6b Listing Unique Values 292 7-6c Aggregate Functions 292 7-6d Grouping Data 297

7-7 Joining Database Tables 300

7-7a Joining Tables with an Alias 303 7-7b Recursive Joins 303

Summary 305 • Key Terms 306 • Review Questions 306 • Problems 307 • Cases 331

Chapter 8: Advanced SQL 340 8-1 SQL Join Operators 341

8-1a Cross Join 342 8-1b Natural Join 343 8-1c JOIN USING Clause 344 8-1d JOIN ON Clause 345 8-1e Outer Joins 347

8-2 Subqueries and Correlated Queries 349 8-2a WHERE Subqueries 351 8-2b IN Subqueries 352

viii Contents

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8-2c HAVING Subqueries 353 8-2d Multirow Subquery Operators: ANY and ALL 353 8-2e FROM Subqueries 355 8-2f Attribute List Subqueries 356 8-2g Correlated Subqueries 358

8-3 SQL Functions 361

8-3a Date and Time Functions 361 8-3b Numeric Functions 366 8-3c String Functions 366 8-3d Conversion Functions 368

8-4 Relational Set Operators 371 8-4a UNION 371 8-4b UNION ALL 373 8-4c INTERSECT 373 8-4d EXCEPT (MINUS) 375 8-4e Syntax Alternatives 377

8-5 Virtual Tables: Creating a View 377 8-5a Updatable Views 379

8-6 Sequences 382 8-7 Procedural SQL 387

8-7a Triggers 392 8-7b Stored Procedures 401 8-7c PL/SQL Processing with Cursors 407 8-7d PL/SQL Stored Functions 409

8-8 Embedded SQL 410 Summary 415 • Key Terms 416 • Review Questions 417 • Problems 418 • Cases 435

Chapter 9: Database Design 439 9-1 The Information System 440 9-2 The Systems Development Life Cycle 442 9-2a Planning 442 9-2b Analysis 443 9-2c Detailed Systems Design 444 9-2d Implementation 444 9-2e Maintenance 445

9-3 The Database Life Cycle 445

9-3a The Database Initial Study 445 9-3b Database Design 450 9-3c Implementation and Loading 451 9-3d Testing and Evaluation 454 9-3e Operation 456 9-3f Maintenance and Evolution 457

9-4 Conceptual Design 457

9-4a Data Analysis and Requirements 459 9-4b Entity Relationship Modeling and Normalization 461 9-4c Data Model Verification 464 9-4d Distributed Database Design 467

9-5 DBMS Software Selection 467 9-6 Logical Design 468

9-6a Map the Conceptual Model to the Logical Model 468 9-6b Validate the Logical Model Using Normalization 470 9-6c Validate Logical Model Integrity Constraints 470 9-6d Validate the Logical Model Against User Requirements 471

9-7 Physical Design 471

9-7a Define Data Storage Organization 472 9-7b Define Integrity and Security Measures 472 9-7c Determine Performance Measures 473

9-8 Database Design Strategies 473 9-9 Centralized Versus Decentralized Design 474 Summary 477 • Key Terms 477 • Review Questions 477 • Problems 478

Contents ix

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Part 4: Advanced Database Concepts 481 Chapter 10: Transaction Management and Concurrency Control 482 10-1 What Is a Transaction? 483

10-1a Evaluating Transaction Results 484 10-1b Transaction Properties 487 10-1c Transaction Management with SQL 488 10-1d The Transaction Log 489

10-2 Concurrency Control 490

10-2a Lost Updates 490 10-2b Uncommitted Data 491 10-2c Inconsistent Retrievals 492 10-2d The Scheduler 493

10-3 Concurrency Control with Locking Methods 495

10-3a Lock Granularity 496 10-3b Lock Types 498 10-3c Two-Phase Locking to Ensure Serializability 500 10-3d Deadlocks 500

10-4 Concurrency Control with Time Stamping Methods 502 10-4a Wait/Die and Wound/Wait Schemes 502

10-5 Concurrency Control with Optimistic Methods 503 10-6 ANSI Levels of Transaction Isolation 504 10-7 Database Recovery Management 506 10-7a Transaction Recovery 506

Summary 510 • Key Terms 511 • Review Questions 511 • Problems 512

Chapter 11: Database Performance Tuning and Query Optimization 515 11-1 Database Performance-Tuning Concepts 516

11-1a Performance Tuning: Client and Server 517 11-1b DBMS Architecture 518 11-1c Database Query Optimization Modes 520 11-1d Database Statistics 521

11-2 Query Processing 522

11-2a SQL Parsing Phase 523 11-2b SQL Execution Phase 524 11-2c SQL Fetching Phase 525 11-2d Query Processing Bottlenecks 525

11-3 Indexes and Query Optimization 526 11-4 Optimizer Choices 528

11-4a Using Hints to Affect Optimizer Choices 530

11-5 SQL Performance Tuning 531

11-5a Index Selectivity 531 11-5b Conditional Expressions 533

11-6 Query Formulation 534 11-7 DBMS Performance Tuning 536 11-8 Query Optimization Example 538 Summary 546 • Key Terms 547 • Review Questions 547 • Problems 548

Chapter 12: Distributed Database Management Systems 553 12-1 The Evolution of Distributed Database Management Systems 554 12-2 DDBMS Advantages and Disadvantages 556 12-3 Distributed Processing and Distributed Databases 556 12-4 Characteristics of Distributed Database Management Systems 559 12-5 DDBMS Components 560 12-6 Levels of Data and Process Distribution 561 12-6a Single-Site Processing, Single-Site Data 561 12-6b Multiple-Site Processing, Single-Site Data 562 12-6c Multiple-Site Processing, Multiple-Site Data 563

12-7 Distributed Database Transparency Features 564 12-8 Distribution Transparency 565

x Contents

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12-9 Transaction Transparency 568

12-9a Distributed Requests and Distributed Transactions 568 12-9b Distributed Concurrency Control 571 12-9c Two-Phase Commit Protocol 571

12-10 Performance and Failure Transparency 573 12-11 Distributed Database Design 575 12-11a Data Fragmentation 575 12-11b Data Replication 578 12-11c Data Allocation 580

12-12 The CAP Theorem 581 12-13 C. J. Date’s 12 Commandments for Distributed Databases 583 Summary 584 • Key Terms 585 • Review Questions 585 • Problems 586

Chapter 13: Business Intelligence and Data Warehouses 589 13-1 The Need for Data Analysis 590 13-2 Business Intelligence 590

13-2a Business Intelligence Architecture 592 13-2b Business Intelligence Benefits 598 13-2c Business Intelligence Evolution 598 13-2d Business Intelligence Technology Trends 601

13-3 Decision Support Data 602

13-3a Operational Data Versus Decision Support Data 602 13-3b Decision Support Database Requirements 605

13-4 The Data Warehouse 607

13-4a Data Marts 610 13-4b Twelve Rules That Define a Data Warehouse 610

13-5 Star Schemas 610

13-5a Facts 611 13-5b Dimensions 611 13-5c Attributes 612 13-5d Attribute Hierarchies 614 13-5e Star Schema Representation 616 13-5f Performance-Improving Techniques for the Star Schema 617

13-6 Online Analytical Processing 621

13-6a Multidimensional Data Analysis Techniques 621 13-6b Advanced Database Support 623 13-6c Easy-to-Use End-User Interfaces 623 13-6d OLAP Architecture 623 13-6e Relational OLAP 626 13-6f Multidimensional OLAP 628 13-6g Relational versus Multidimensional OLAP 628

13-7 SQL Extensions for OLAP 629

13-7a The ROLLUP Extension 630 13-7b The CUBE Extension 631 13-7c Materialized Views 633

Summary 636 • Key Terms 637 • Review Questions 637 • Problems 639

Chapter 14: Big Data Analytics and NoSQL 648 14-1 Big Data 649

14-1a Volume 651 14-1b Velocity 652 14-1c Variety 653 14-1d Other Characteristics 654

14-2 Hadoop 655

14-2a HDFS 655 14-2b MapReduce 658 14-2c Hadoop Ecosystem 660

14-3 NoSQL 662

14-3a Key-Value Databases 663 14-3b Document Databases 664 14-3c Column-Oriented Databases 665 14-3d Graph Databases 668 14-3e NewSQL Databases 669

Contents xi

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14-4 Data Analytics 670

14-4a Data Mining 671 14-4b Predictive Analytics 673

Summary 675 • Key Terms 676 • Review Questions 677

Part 5: Databases and the Internet 679 Chapter 15: Database Connectivity and Web Technologies 680 15-1 Database Connectivity 681

15-1a Native SQL Connectivity 682 15-1b ODBC, DAO, and RDO 683 15-1c OLE-DB 685 15-1d ADO.NET 687 15-1e Java Database Connectivity (JDBC) 691

15-2 Database Internet Connectivity 692

15-2a Web-to-Database Middleware: Server-Side Extensions 693 15-2b Web Server Interfaces 695 15-2c The Web Browser 696 15-2d Client-Side Extensions 697 15-2e Web Application Servers 698 15-2f Web Database Development 699

15-3 Extensible Markup Language (XML) 702

15-3a Document Type Definitions (DTD) and XML Schemas 704 15-3b XML Presentation 706 15-3c XML Applications 708

15-4 Cloud Computing Services 709

15-4a Cloud Implementation Types 712 15-4b Characteristics of Cloud Services 712 15-4c Types of Cloud Services 713 15-4d Cloud Services: Advantages and Disadvantages 714 15-4e SQL Data Services 716

Summary 717 • Key Terms 718 • Review Questions 718 • Problems 719

Part 6: Database Administration 721 Chapter 16: Database Administration and Security 722 16-1 Data as a Corporate Asset 723 16-2 The Need for a Database and its Role in an Organization 724 16-3 Introduction of a Database: Special Considerations 726 16-4 The Evolution of Database Administration 727 16-5 The Database Environment’s Human Component 731 16-5a The DBA’s Managerial Role 733 16-5b The DBA’s Technical Role 738

16-6 Security 745

16-6a Security Policies 746 16-6b Security Vulnerabilities 746 16-6c Database Security 748

16-7 Database Administration Tools 749 16-7a The Data Dictionary 750 16-7b Case Tools 752

16-8 Developing a Data Administration Strategy 755 16-9 The DBA’s Role in the Cloud 756 16-10 The DBA at Work: Using Oracle for Database Administration 757 16-10a Oracle Database Administration Tools 758 16-10b Ensuring that the RDBMS Starts Automatically 758 16-10c Creating Tablespaces and Datafiles 760 16-10d Managing Users and Establishing Security 762 16-10e Customizing the Database Initialization Parameters 763

Summary 765 • Key Terms 766 • Review Questions 767 Glossary 769 Index 783

xii Contents

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The following appendixes are included on the Instructor and Student Companion Sites at www.cengagebrain.com.

Appendix A1: Designing Databases with Visio Professional 2010: A Tutorial Appendix A2: Designing Databases with Visio 2013: A Tutorial Appendix B: The University Lab: Conceptual Design Appendix C: The University Lab: Conceptual Design Verification, Logical Design, and Implementation Appendix D: Converting an ER Model into a Database Structure Appendix E: Comparison of ER Model Notations Appendix F: Client/Server Systems Appendix G: Object-Oriented Databases Appendix H: Unified Modeling Language (UML) Appendix I: Databases in Electronic Commerce Appendix J: Web Database Development with ColdFusion Appendix K: The Hierarchical Database Model Appendix L: The Network Database Model Appendix M: MS Access Tutorial Appendix N: Creating a New Database Using Oracle 12c Appendix O: Data Warehouse Implementation Factors

Contents xiii

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Preface It is our great pleasure to present the twelfth edition of Database Systems. We are grateful and humbled that so many of our colleagues around the world have chosen this text to support their classes. We wrote the first edition of this book because we wanted to explain the complexity of database systems in a language that was easy for students to understand. Over the years, we have maintained this emphasis on reaching out to students to explain complex concepts in a practical, approachable manner. This book has been successful through eleven editions because the authors, editors, and the publisher paid attention to the impact of technology and to adopter questions and suggestions. We believe that this twelfth edition successfully reflects the same attention to such factors.

In many respects, rewriting a book is more difficult than writing it the first time. If the book is successful, as this one is, a major concern is that the updates, inserts, and deletions will adversely affect writing style and continuity of coverage. The combination of superb reviewers and editors, plus a wealth of feedback from adopters and students of the previous editions, helped make this new edition the best yet.

Changes to The Twelfth Edition

In this twelfth edition, we added some new features and reorganized some coverage to provide a better flow of material. Aside from enhancing the already strong coverage of database design, we made other improvements in the topical coverage. In particular, the continued growth of Big Data and NoSQL technologies have challenged the status quo in the database industry. Therefore, we created an entire new chapter, Big Data Analytics and NoSQL, to help students grasp the key aspects of these complex new technologies and challenges. The twelfth edition also presents a major step forward in the integration of digital content with the text through online, automatically graded exercises to improve student outcomes. Here are a few of the highlights of changes in the twelfth edition:

• • • •

New coverage of Big Data challenges beyond the traditional 3Vs

• • • •

New coverage of the emerging NewSQL technologies

Expanded coverage of Hadoop, the Hadoop Distributed File System (HDFS), and MapReduce Updated coverage of cloud data services and their impact on DBAs Expanded coverage of NoSQL databases, including key-value databases, document databases, column-oriented database, and graph databases Improved coverage of data visualization Added coverage of new sequence and identity capabilities in Oracle and SQL Server Complete redesign of the look and feel of the text and layout to improve readability and visual appeal

• Embedded key term definitions within the text This twelfth edition continues to provide a solid and practical foundation for the design, implementation, and management of database systems. This foundation is built on the notion that, while databases are very practical, their successful creation depends on understanding the important concepts that define them. It’s not easy to come up with the proper mix of theory and practice, but the previously mentioned feedback suggests that we largely succeeded in our quest to maintain the proper balance.

xiv Preface

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The Approach: A Continued Emphasis On Design

As the title suggests, Database Systems: Design, Implementation, and Management covers three broad aspects of database systems. However, for several important reasons, special attention is given to database design.

• The availability of excellent database software enables people with little experience to cre-

ate databases and database applications. Unfortunately, the “create without design” approach usually paves the road to a number of database disasters. In our experience, many database system failures are traceable to poor design and cannot be solved with the help of even the best programmers and managers. Nor is better DBMS software likely to overcome problems created or magnified by poor design. Even the best bricklayers and carpenters can’t create a good building from a bad blueprint.

• Most vexing problems of database system management seem to be triggered by poorly designed databases. It hardly seems worthwhile to use scarce resources to develop excellent database management skills merely to use them on crises induced by poorly designed databases.

• Design provides an excellent means of communication. Clients are more likely to get what they

need when database system design is approached carefully and thoughtfully. In fact, clients may discover how their organizations really function once a good database design is completed.

• Familiarity with database design techniques promotes understanding of current database

technologies. For example, because data warehouses derive much of their data from operational databases, data warehouse concepts, structures, and procedures make more sense when the operational database’s structure and implementation are understood.

Because the practical aspects of database design are stressed, we have covered design concepts and procedures in detail, making sure that the numerous end-of-chapter problems and cases are sufficiently challenging so students can develop real and useful design skills. We also make sure that students understand the potential and actual conflicts between database design elegance, information requirements, and transaction processing speed. For example, it makes little sense to design databases that meet design elegance standards while they fail to meet end-user information requirements. Therefore, we explore the use of carefully defined trade-offs to ensure that the databases meet end-user requirements while conforming to high design standards.

Topical Coverage The Systems View

The book’s title begins with Database Systems. Therefore, we examine the database and design concepts covered in Chapters 1–6 as part of a larger whole by placing them within the systems analysis framework of Chapter 9. Database designers who fail to understand that the database is part of a larger system are likely to overlook important design requirements. In fact, Chapter 9, Database Design, provides the map for the advanced database design developed in Appendixes B and C. Within the larger systems framework, we can also explore issues such as transaction management and concurrency control (Chapter 10), distributed database management systems (Chapter 12), business intelligence and data warehouses (Chapter 13), database connectivity and web technologies (Chapter 15), and database administration and security (Chapter 16).

PART 1 Database Concepts 1 Database Systems 2 Data Models Preface xv

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Database Design

The first item in the book’s subtitle is Design, and our examination of database design is comprehensive. For Chapter 9 example, Chapters 1 and 2 examine the development and future of databases and data models, and illustrate Database Design the need for design. Chapter 3 examines the details of In this chapter, you will learn: • That a sound database design is the foundation for a successful information system, and that the the relational database model; Chapter 4 provides exdatabase design must reflect the information system of which the database is a part • That successful information systems are developed within a framework known as the Systems tensive, in-depth, and practical database design coverDevelopment Life Cycle (SDLC) • That within the information system, the most successful databases are subject to frequent age; and Chapter 5 explores advanced database design evaluation and revision within a framework known as the Database Life Cycle (DBLC) • How to conduct evaluation and revision within the SDLC and DBLC frameworks topics. Chapter 6 is devoted to critical normalization • About database design strategies: top-down versus bottom-up design and centralized versus decentralized design issues that affect database efficiency and effectiveness.

Databases are a part of a larger picture called an information system. Database designs Chapter 9 examines database design within the systems Preview that fail to recognize this fact are not likely to be successful. Database designers must recognize that the database is a critical means to an end rather than an end in itself. Managers framework and maps the activities required to successwant the database to serve their management needs, but too many databases seem to force managers to alter their routines to fit the database requirements. fully design and implement the complex, real-world Information systems don’t just happen; they are the product of a carefully staged development process. Systems analysis is used to determine the need for an information system database developed in Appendixes B and C. Appendix and to establish its limits. Within systems analysis, the actual information system is created through a process known as systems development.

A, Designing Databases with Visio Professional: A TuThe creation and evolution of information systems follows an iterative pattern called the Systems Development Life Cycle (SDLC), which is a continuous process of creation, torial, provides a good introductory tutorial for the use maintenance, enhancement, and replacement of the information system. A similar cycle applies to databases: the database is created, maintained, enhanced, and eventually of a database design tool. replaced. The Database Life Cycle (DBLC) is carefully traced in this chapter, and is shown in the context of the larger Systems Development Life Cycle.

Because database design is affected by real-world At the end of the chapter, you will be introduced to some classical approaches to database design: top-down versus bottom-up and centralized versus decentralized. transactions, the way data is distributed, and ever-increasing information requirements, we examine major database features that must be supported in current-genData Files Available on cengagebrain.com eration databases and models. For example, Chapter 10, Note Transaction Management and Concurrency Control, Because it is purely conceptual, this chapter does not reference any data files. focuses on the characteristics of database transactions and how they affect database integrity and consistency.

Chapter 11, Database Performance Tuning and Query Optimization, illustrates the need for query efficiency in a world that routinely generates and uses terabyte-size databases and tables with millions of records. Chapter 12, Distributed Database Management Systems, focuses on data distribution, replication, and allocation. In Chapter 13, Business Intelligence and Data Warehouses, we explore the characteristics of databases that are used in decision support and online analytical processing. Chapter 14, Big Data Analytics and NoSQL, explores the challenges of designing nonrelational databases to use vast global stores of unstructured data. Chapter 15, Database Connectivity and Web Technologies, covers the basic database connectivity issues in a web-based data world, development of web-based database front ends, and emerging cloud-based services.

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Implementation

PART 3 Advanced Design and Implementation 7 Introduction to Structured Query Language (SQL) 8 Advanced SQL 9 Database Design

The second portion of the subtitle is Implementation.

We use Structured Query Language (SQL) in Chapters 7 and 8 to show how relational databases are implemented and managed. Appendix M, Microsoft Access Tutorial, provides a quick but comprehensive guide to implementing an MS Access database. Appendixes B and C demonstrate the design of a database that was fully implemented; these appendixes ­illustrate a wide range of implementation issues.

We had to deal with conflicting design goals: design elegance, information requirements, and operational speed. Therefore, we carefully audited the initial design in Appendix B to check its ability to meet end-user needs and establish appropriate implementation protocols. The result of this audit yielded the final design developed in Appendix C. While relational databases are still the appropriate database technology to use in the vast majority of situations, Big Data issues have created an environment in which special

xvi Preface

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requirements can call for the use of new, nonrelational technologies. Chapter 14, Big Data Analytics and NoSQL, describes the types of data that are appropriate for these new technologies and the array of options available in these special cases. The special issues encountered in an Internet database environment are addressed in Chapter 15, Database Connectivity and Web Technologies, and in Appendix J, Web Database Development with ColdFusion.

Management

The final portion of the subtitle is Management. We deal with database management issues in Chapter 10, Transaction Management and Concurrency Control; Chapter 12, Distributed Database Management Systems; and Chapter 16, Database Administration and Security. Chapter 11, Database Performance Tuning and Query Optimization, is a valuable resource that illustrates how a DBMS manages data retrieval. In addition, Appendix N, Creating a New Database Using Oracle 12c, walks you through the process of setting up a new database.

PART 6 Database Administration 16 Database Administration and Security

Teaching Database: A Matter of Focus

Given the wealth of detailed coverage, instructors can “mix and match” chapters to produce the desired coverage. Depending on where database courses fit into the curriculum, instructors may choose to emphasize database design or database management. (See Figure 1.)

The hands-on nature of database design lends itself particularly well to class projects in which students use instructor-selected software to prototype a system that they design for the end user.

Several end-of-chapter problems are sufficiently complex to serve as projects, or an instructor may work with local businesses to give students hands-on experience. Note that some elements of the database design track are also found in the database management track, because it is difficult to manage database technologies that are not well understood.

The options shown in Figure 1 serve only as a starting point. Naturally, instructors will tailor their coverage based on their specific course requirements. For example, an instructor may decide to make Appendix I an outside reading assignment and make Appendix A a self-taught tutorial, and then use that time to cover client/server systems or object-oriented databases. The latter choice would serve as a gateway to UML coverage.

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Preface xvii

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).

Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.

FIGURE 1

Core Coverage (1) Database Systems (2) Data Models (3) The Relational Database Model (4) Entity Relationship (ER) Modeling (6) Normalization of Database Tables (7) Introduction to Structured Query Language (SQL)

Database Design and Implementation Focus

Database Management Focus

(5) Advanced Data Modeling (8) Advanced SQL (9) Database Design (A) Designing Databases with Visio Professional (D) Converting an ER Model into a Database Structure (E) Comparison of ER Model Notations (H) Unified Modeling Language (UML) (14) Big Data Analytics and NoSQL (15) Database Connectivity and Web Technologies

(10) Transaction Management and Concurrency Control (11) Database Performance Tuning and Query Optimization (12) Distributed Database Management Systems (13) Business Intelligence and Data Warehouses (15) Database Connectivity and Web Technologies (16) Database Administration and Security (F) Client/Server Systems (G) Object Oriented Databases

Supplementary Reading

Supplementary Reading

(B) The University Lab: Conceptual Design (C) The University Lab: Conceptual Design Verification, Logical Design, and Implementation (M) Microsoft Access Tutorial (J) Web Database Development with ColdFusion (K) The Hierarchical Database Model (L) The Network Database Model

(9) Database Design (M) Microsoft Access Tutorial (N) Creating a New Database Using Oracle 12c (O) Data Warehouse Implementation Factors (I) Databases in Electronic Commerce (J) Web Database Development with ColdFusion

xviii Preface

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).

Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.

ber name name le initial of birth earned ification average ferred from another institution code us phone extension e professor who is the student’s advisor

78 Part 2 Design Concepts

TABLE 3.2 STUDENT CLASSIFICATION

Text Features

n in Figure 3.1, you can draw the following concluOnline Content boxes Table 3.1:

draw attention to material ed to be a two-dimensional structure composed of at www.cengagebrain.com s (attributes). for this text and provide ideasoccurrence for incorporating ble describes a single entity within the this content into the resented by the STUDENT table.) For example, row course.

ent named Walter H. Oblonski. Given the table conncludes eight distinct entities (rows), or students.

ibute, and each column has a distinct name.

match the attribute’s characteristics. For example, GPA) column contains only STU_GPA entries for ust be classified according to its format and funcs can support different data types, most support at

ic data to perform meaningful arithmetic procedures.

TU_HRS and STU_GPA are numeric attributes.

Notes highlights

­important so known as text data or string data,facts canabout contain any the concepts nded for mathematical manipulation.introduced In Figure 3.1, in the chapter.

NE are examples of character attributes.

n calendar dates stored in a special format known as gure 3.1, STU_DOB is a date attribute.

y have true or false (yes or no) values. In Figure 3.1, ute uses a logical data format.

variety of four-color sible values is known asAits domain.

Because the figures, including o the range 0–4, inclusive, the domain is [0,4].

ER models and

is immaterial to the user. implementations,

tables, and illustrations, clearly illustrate difficult concepts.

Online Content All of the databases used to illustrate the material in this chapter (see the Data Files list at the beginning of the chapter) are available at www.cengagebrain. com. The database names match the database names shown in the figures.

HOURS COMPLETED

CLASSIFICATION

Less than 30

Fr

30–59

So

60–89

Jr

90 or more

Sr

One specific type of superkey is called a candidate key. A candidate key i superkey—that is, a superkey without any unnecessary attributes. A cand based on a full functional dependency. For example, STU_NUM would be key, as would (STU_LNAME, STU_FNAME, STU_INIT, STU_PHONE). O hand, (STU_NUM, STU_LNAME) is a superkey, but it is not a candidate k STU_LNAME could be removed and the key would still be a superkey. A tab many different candidate keys. If the STUDENT table also included the stud Security numbers as STU_SSN, then it would appear to be a candidate key keys are called candidates because they are the eligible options from which t will choose when selecting the primary key. The primary key is the candidate to be the primary means by which the rows of the table are uniquely identifie Entity integrity is the condition in which each row (entity instance) in th its own unique identity. To ensure entity integrity, the primary key has two req (1) all of the values in the primary key must be unique, and (2) no key attr primary key can contain a null.

Note A null is no value at all. It does not mean a zero or a space. A null is created when you press the Enter key or the Tab key to move to the next entry without making an entry of any kind.

Pressing tuple the Spacebar creates a blank (or a space).

In the relational model, a table row.

domain

1 Databasemodel.

Systems 25 Null values are problematic in Chapter the relational A null is the abse

In data modeling, data value, and it is never allowed in any part of the primary key. From a the construct used to FIGURE 1.11 ILLUSTRATING METADATA WITH MICROSOFT SQL SERVER EXPRESS organize and describe an perspective, it can be argued that a table that contains a null is not properly attribute’s set of possible table at all. From a practical perspective, however, some nulls cannot be candidate values. key avoided. For example, not all students have a middle initial. As a general A minimal superkey; should be avoided as much as reasonably possible. In fact, an abundance that is, a key that does often a sign of a poor design. Also, nulls should be avoided in the databa not contain a subset of attributes that is itself a their meaning is not always identifiable. For example, a null could represen superkey. See key. following:

entity integrity

The property of a relational table that guarantees each entity has a unique value in a primary key and that the key has no null values.

• An unknown attribute value

19/12/15 11:40 AM

null The absence of an attribute value. Note that a null is not a blank.

• A known, but missing, attribute value • A “not applicable” condition

Depending on the sophistication of the application development softwar create problems when functions such as COUNT, AVERAGE, and SUM a addition, nulls can create logical problems when relational tables are linked.

In addition to its role in providing a unique identity to each row in th primary key may play an additional role in the controlled redundancy that

Text Features xix access the data in the database work through the DBMS. The DBMS uses the data dictionary to look up the required data component structures and relationships, thus relieving you from having to78code such complex relationships in each proBK-CHE-CORONEL_MORRIS_12E-150049-Chp03.indd Additionally, any changes in a rights, database are automatically Copyright 2017 Cengage Learning. All Rights Reserved. May gram. not be copied, scanned, or duplicated, in whole or in part.made Due to electronic some thirdstructure party content may be suppressed from the eBook and/or eChapter(s).

Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it. recorded in the data dictionary, thereby freeing you from having to modify all of the programs that access the changed structure. In other words, the DBMS provides data abstraction, and it removes structural and data dependence from the system.

For example, Figure 1.11 shows how Microsoft SQL Server Express presents the

for an information system and its extent. Systems development is the process of creating an information system.

• The Systems Development Life Cycle (SDLC) traces the history of an application Chapter 9 Database Design 477 within the information system. The SDLC can be divided into five phases: planning, analysis, detailed systems design, implementation, and maintenance. The SDLC is an A robust Summary at iterative process rather than a sequential process. the end of each chapter

Summary

• The Database Life Cycle (DBLC) describes the history of the database within the information system. The DBLC is composed of six phases: database initial study, database • An information system is designed help transform data into information to design, implementation and loading,totesting and evaluation, operation, and and mainmanage bothevolution. data and Like information. the database is arather very important part of tenance and the SDLC,Thus, the DBLC is iterative than sequential. the information system. Systems analysis is the process that establishes the need • The conceptual portion of the design may be subject to several variations based on for an information system and its extent. Systems development is the process of two basic design philosophies: bottom-up versus top-down and centralized versus creating an information system. decentralized.

• The Systems Development Life Cycle (SDLC) traces the history of an application within the information system. The SDLC can be divided into five phases: planning, analysis, detailed systems design, implementation, and maintenance. The SDLC is an iterative process rather than a sequential process.

Key Terms

ties together the major concepts and serves as a quick review for students.

An alphabetic list of Key Terms summarizes important terms.

design Database Life Cycle (DBLC)of themodule coupling • bottom-up The Database Life Cycle (DBLC) describes the history database within the information system. The DBLC isdatabase composed initial study, databaseOnline boundaries roleof six phases: database physical design design, implementation and loading, testing and evaluation, operation, and main-Content centralized design decentralized design scope tenance and evolution. Like the SDLC, the DBLC is iterative rather than sequential. clustered tables

description of operations

systems analysis

Flashcards and crossword

• The conceptual portion of the design may be subject to several variations based onpuzzles for key term practice cohesivity differential backup systems development two basic design philosophies: bottom-up versus top-down and centralized versusare available at ChapterSystems 15 Database Connectivity and Web Technologies 719 computer-aided full backup Development decentralized. software www.cengagebrain.com. engineering (CASE)

information system

Life Cycle (SDLC)

system 14. What is a web applicationinformation server, and how does it work from a database conceptual design top-down design logical design perspective?

database development transaction log backup Key Terms minimal data rule 15. What are scripts, and what is their function?

(Think in terms of database database fragment application development.) module bottom-up design Database Life Cycle (DBLC)

16.

What is XML, and why is itdatabase important? boundaries role

virtualization module coupling physical design

17.

What aredesign document type definition (DTD) documents, and what do they do? centralized decentralized design scope

Online Content The Ch02 databases used in the Problems for this chapter are available at www. cengagebrain.com.

clustered tables description of operations 18.

What are XML schema definition (XSD) documents, andsystems what doanalysis they do?

Review Questions cohesivity 19.

What is JDBC, and what is differential it used for?backup

systems development

Online Content

Flashcards crossword Reviewand Questions puzzles for keystudents term practice ­challenge to are available apply theatskills learned www.cengagebrain.com. in each chapter.

computer-aided full backup Systems Development 20.

What is cloudsoftware computing, and why is it a “game changer”? engineering (CASE) Life Cycle (SDLC) 1. What is an information system?

What is its purpose? information system 21. Name and contrast the types of cloud computing implementation. top-down design 2.conceptual How do design systems analysis and systems development fit into a discussion about inforlogical design 22. Name and describe the most prevalent characteristics of cloud computing services. mationdevelopment systems? database transaction log backup minimal data rule 23.

Using the Internet, search for providers of cloud services.

Then, classify the types of fragment virtualization 3.database What does the acronym SDLC mean, and what does an SDLC portray? services they provide (SaaS,module PaaS, and IaaS).

4. What does the acronym DBLC mean, and what does a DBLC portray?

24. Summarize the main advantages and disadvantages of cloud computing services.

5. Discuss the distinction between centralized and decentralized conceptual database 25. Define SQL data services and list their advantages. design.

Review Questions

Problems 1.

What is an information system? What is its purpose?

2. How do systems analysis and systems development fit into a discussion about information systems?

In the following exercises, you will set up database connectivity using MS Excel.

BK-CHE-CORONEL_MORRIS_12E-150049-Chp09.indd 477

3. Use What does theto acronym and what does SDLC portray?using ODBC, 1.

MS Excel connectSDLC to themean, Ch02_InsureCo MS an Access database retrieve all acronym of the AGENTs. 4. and What does the DBLC mean, and what does a DBLC portray?

Problems become ­progressively more ­complex as students draw on the lessons19/12/15 11:55 AM learned from the ­completion of preceding problems.

2.

MS the Excel to connect to the Ch02_InsureCo Access database usingdatabase ODBC, 5. Use Discuss distinction between centralized and MS decentralized conceptual and retrieve all of the CUSTOMERs. design.

3. Use MS Excel to connect to the Ch02_InsureCo MS Access database using ODBC,

xx Text andFeatures retrieve the customers whose AGENT_CODE is equal to 503.

4. Create a System DSN ODBC connection called Ch02_SaleCo using the AdministraCopyrightsection 2017 Cengage Learning.

All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s). tive Editorial Tools of the Windows Control Panel. review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.

BK-CHE-CORONEL_MORRIS_12E-150049-Chp09.indd 477

5. Use MS Excel to list all of the invoice lines for Invoice 103 using the Ch02_SaleCo System DSN.

19/12/15 11:55 AM

Additional Features MindTap® for Database Systems 12e

MindTap® combines learning tools—such as readings, multimedia, activities, and assessments— into a singular learning path that guides students through the course. You’ll find a full ebook as well as a robust set of auto-gradable homework problems. Multiple-choice homework questions developed from the end-of-chapter review questions confirm students’ understanding of core concepts and key terms. Higher-level assignments enable students to practice database design concepts in an automated environment, and chapter quizzes help prepare students for exams.

Students will also benefit from the chapter-opening videos created by the authors, as well as study tools such as crossword puzzles and key-term flashcards.

MindTap® is designed to be fully integrated with any Learning Management System and can be used as a stand-alone product or in conjunction with a print textbook.

Appendixes

Fifteen online appendixes provide additional material on a variety of important areas, such as using Microsoft® Visio® and Microsoft® Access®, ER model notations, UML, object-oriented databases, databases and electronic commerce, and Adobe® ColdFusion®.

Database, SQL Script, and ColdFusion Files

The online materials for this book include all of the database structures and table contents used in the text. For students using Oracle®, MySQL, and Microsoft SQL Server™, SQL scripts are included to help students create and load all tables used in the SQL chapters (7 and 8). In addition, all ColdFusion scripts used to develop the web interfaces in Appendix J are included.

Instructor Resources

Database Systems: Design, Implementation, and Management, Twelfth Edition, includes teaching tools to support instructors in the classroom. The ancillary material that accompanies the textbook is listed below. They are available on the web at www.cengagebrain.com.

Instructor’s Manual

The authors have created this manual to help instructors make their classes informative and interesting. Because the authors tackle so many problems in depth, instructors will find the Instructor’s Manual especially useful. The details of the design solution process are shown in the Instructor’s Manual, as well as notes about alternative approaches that may be used to solve a particular problem.

SQL Script Files for Instructors

The authors have provided teacher’s SQL script files to allow instructors to cut and paste the SQL code into the SQL windows. (Scripts are provided for Oracle, MySQL, and MS SQL Server.)

The SQL scripts, which have all been tested by Cengage Learning, are a major convenience for instructors. You won’t have to type in the SQL commands, and the use of the scripts eliminates typographical errors that are sometimes difficult to trace.

ColdFusion Files for Instructors

The ColdFusion web development solutions are provided. Instructors have access to a menudriven system that allows teachers to show the code as well as its execution.

Additional Features xxi

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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.

Databases

For many chapters, Microsoft® Access® instructor databases are available that include features not found in the student databases. For example, the databases that accompany Chapters 7 and 8 include many of the queries that produce the problem solutions. Other Access databases, such as the ones that accompany Chapters 3, 4, 5, and 6, include implementations of the design problem solutions to allow instructors to illustrate the effect of design decisions. In addition, instructors have access to all the script files for Oracle, MySQL, and MS SQL Server so that all the databases and their tables can be converted easily and precisely.

Cengage Learning Testing Powered by Cognero A flexible, online system that allows you to:

• Author, edit, and manage test bank content from multiple Cengage Learning solutions • Create multiple test versions in an instant • Deliver tests from your LMS, your classroom, or wherever you want Start right away!

Cengage Learning Testing Powered by Cognero works on any operating system or browser.

• No special installs or downloads needed • Create tests from school, home, the coffee shop—anywhere with Internet access What will you find?

• Simplicity at every step. A desktop-inspired interface features drop-down menus and familiar, intuitive tools that take you through content creation and management with ease.

• Full-featured test generator. Create ideal assessments with your choice of 15 question types

(including true/false, multiple-choice, opinion scale/Likert, and essay). Multi-language support, an equation editor, and unlimited metadata help ensure your tests are complete and compliant.

• Cross-compatible capability. Import and export content into other systems.

PowerPoint® Presentations

Microsoft PowerPoint slides are included for each chapter. Instructors can use the slides in a variety of ways—for example, as teaching aids during classroom presentations or as printed handouts for classroom distribution. Instructors can modify these slides or include slides of their own for additional topics introduced to the class.

Figure Files

Figure files for solutions are presented in the Instructor’s Manual to allow instructors to create their own presentations. Instructors can also manipulate these files to meet their particular needs.

xxii Additional Features

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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.

Acknowledgments Regardless of how many editions of this book are published, they will always rest on the solid foundation created by the first edition. We remain convinced that our work has become successful because that first edition was guided by Frank Ruggirello, a former Wadsworth senior editor and publisher. Aside from guiding the book’s development, Frank also managed to solicit the great Peter Keen’s evaluation (thankfully favorable) and subsequently convinced Peter Keen to write the foreword for the first edition. Although we sometimes found Frank to be an especially demanding taskmaster, we also found him to be a superb professional and a fine friend. We suspect Frank will still see his fingerprints all over our current work. Many thanks.

A difficult task in rewriting a book is deciding what new approaches, topical coverage, and changes to depth of coverage are appropriate for a product that has successfully weathered the test of the marketplace. The comments and suggestions made by the book’s adopters, students, and reviewers play a major role in deciding what coverage is desirable and how that coverage is to be treated.

Some adopters became extraordinary reviewers, providing incredibly detailed and well-reasoned critiques even as they praised the book’s coverage and style. Dr. David Hatherly, a superb database professional who is a senior lecturer in the School of Information Technology, Charles Sturt University–Mitchell, Bathhurst, Australia, made sure that we knew precisely what issues led to his critiques. Even better for us, he provided the suggestions that made it much easier for us to improve the topical coverage in earlier editions. All of his help was given freely and without prompting on our part. His efforts are much appreciated, and our thanks are heartfelt.

We also owe a debt of gratitude to Professor Emil T. Cipolla, who teaches at St. Mary College.

Professor Cipolla’s wealth of IBM experience turned out to be a valuable resource when we tackled the embedded SQL coverage in Chapter 8.

Every technical book receives careful scrutiny by several groups of reviewers selected by the publisher. We were fortunate to face the scrutiny of reviewers who were superbly qualified to offer their critiques, comments, and suggestions—many of which strengthened this edition. While holding them blameless for any remaining shortcomings, we owe these reviewers many thanks for their contributions:

Mubarak Banisaklher, Bethune Cookman University

Gerald Karush, Southern New Hampshire University

David Bell, Pacific Union College

Michael Kelly, Community College of Rhode Island

Yurii Boreisha, Minnesota State University, Moorhead Laurie Crawford, Franklin University Mel Goetting, Shawnee State University

Timothy Koets, Grand Rapids Community College Klara Nelson, The University of Tampa

Jeff Guan, University of Louisville

Chiso Okafor, Roxbury Community College

William Hochstettler, Franklin University

Brandon Olson, The College of St. Scholastica

Laurene Hutchinson, Louisiana State University, Baton Rouge

James Reneau, Shawnee State University

Nitin Kale, University of Southern California, Los Angeles

Julio Rivera, University of Alabama at Birmingham Acknowledgments xxiii

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).

Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.

Ruth Robins, University of Houston, Downtown Samuel Sambasivam, Azusa Pacific University Paul Seibert, North Greenville University Ronghua Shan, Dakota State University

Andrew Smith, Marian University Antonis Stylianou, University of North Carolina, Charlotte Brian West, University of Louisiana at Lafayette Nathan White, McKendree University

In some respects, writing books resembles building construction: When 90 percent of the work seems done, 90 percent of the work remains to be done. Fortunately for us, we had a great team on our side.

• We are deeply indebted to Deb Kaufmann for her help and guidance. Deb has been everything

we could have hoped for in a development editor and more. Deb has been our editor for almost all the editions of this book, and the quality of her work shows in the attention to detail and the cohesiveness and writing style of the material in this book.

• After writing so many books and twelve editions of this book, we know just how difficult

it can be to transform the authors’ work into an attractive product. The production team, both at Cengage Learning (Nadia Saloom) and Cenveo Publisher Services (Saravanakumar Dharman), have done an excellent job.

• We also owe Jennifer King and Ted Knight, our Content Developers, special thanks for their ability to guide this book to a successful conclusion.

We also thank our students for their comments and suggestions. They are the reason for writing this book in the first place. One comment stands out in particular: “I majored in systems for four years, and I finally discovered why when I took your course.” And one of our favorite comments by a former student was triggered by a question about the challenges created by a real-world information systems job: “Doc, it’s just like class, only easier. You really prepared me well. Thanks!”

Special thanks go to a very unique and charismatic gentleman. For over 20 years, Peter Rob has been the driving force behind the creation and evolution of this book. This book originated as a product of his drive and dedication to excellence. For over 22 years, he was the voice of Database Systems and the driving force behind its advancement. We wish him peace in his retirement, time with his loved ones, and luck on his many projects.

Last, and certainly not least, we thank our families for their solid support at home. They graciously accepted the fact that during more than a year’s worth of rewriting, there would be no free weekends, rare free nights, and even rarer free days. We owe you much, and the dedications we wrote are but a small reflection of the important space you occupy in our hearts.

Carlos Coronel and Steven Morris

xxiv Acknowledgments

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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.

PART 1 Database Concepts 1 Database Systems 2 Data Models

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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.

Chapter 1 Database Systems In this chapter, you will learn: • The difference between data and information • What a database is, the various types of databases, and why they are valuable assets for decision making

• The importance of database design • How modern databases evolved from file systems • About flaws in file system data management • The main components of the database system • The main functions of a database management system (DBMS)

Preview

Organizations use data to keep track of their day-to-day operations. Such data is used to generate information, which in turn is the basis for good decisions. Data is likely to be managed most efficiently when it is stored in a database. Databases are involved in almost all facets and activities of our daily lives: from school, to work, to medical care, government, nonprofit organizations, and houses of worship. In this chapter, you will learn what a database is, what it does, and why it yields better results than other data management methods. You will also learn about various types of databases and why database design is so important.

Databases evolved from computer file systems. Although file system data management is now largely outmoded, understanding the characteristics of file systems is important because file systems are the source of serious data management limitations. In this chapter, you will also learn how the database system approach helps eliminate most of the shortcomings of file system data management.

Data Files and Available Formats MS Access

Oracle

MS SQL

My SQL

P

P

P

P

CH01_Design_Example P

P

P

P

CH01_Text

CH01_Problems

MS Access

Oracle

MS SQL

My SQL

P

P

P

P

Data Files Available on cengagebrain.com

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Editorial review has deemed that any suppressed content does not materially affect the overall learning experience. Cengage Learning reserves the right to remove additional content at any time if subsequent rights restrictions require it.

Chapter 1 Database Systems 3

1-1 Why Databases?

So, why do we need databases? In today’s world, data is ubiquitous (abundant, global, everywhere) and pervasive (unescapable, prevalent, persistent). From birth to death, we generate and consume data. The trail of data starts with the birth certificate and continues all the way to a death certificate (and beyond!). In between, each individual produces and consumes enormous amounts of data. As you will see in this book, databases are the best way to store and manage data. Databases make data persistent and shareable in a secure way. As you look at Figure 1.1, can you identify some of the data generated by your own daily activities?

FIGURE 1.1 THE PERVASIVE NATURE OF DATABASES A Day In Susan’s Life See how many databases she interacts with each day Before leaving for work, Susan checks her Facebook and Twitter accounts

On her lunch break, she picks up her prescription at the pharmacy

After work, Susan goes to the grocery store

At night, she plans for a trip and buys airline tickets and hotel reservations online

Then she makes a few online purchases

C O CA

www.abc.com

Where is the data about the friends and groups stored?

Where is the pharmacy inventory data stored?

Where is the product data stored?

Where are the “likes” stored and what would they be used for?

What data about each product will be in the inventory data?

Is the product quantity in stock updated at checkout?

What data is kept about each customer and where is it stored?

Does she pay with a credit card?

Where does the online travel website get the airline and hotel data from?

What customer data would be kept by the website?

Where would the customer data be stored?

Where are the product and stock data stored?

Where does the system get the data to generate product “recommendations” to the customer?

Where would credit card information be stored?

Users

Products

Products

Flights

Products

Friends

Sales

Sales

Hotels

Sales

Customers

Customers

Customers

Customers

Posts

Data is not only ubiquitous and pervasive, it is essential for organizations to survive and prosper. Imagine trying to operate a business without knowing who your customers are, what products you are selling, who is working for you, who owes you money, and to whom you owe money. All businesses have to keep this type of data and much more.

Just as important, they must have that data available to decision makers when necessary.

It can be argued that the ultimate purpose of all business information systems is to help businesses use information as an organizational resource. At the heart of all of these systems are the collection, storage, aggregation, manipulation, dissemination, and management of data.

Depending on the type of information system and the characteristics of the business, this data could vary from a few megabytes on just one or two topics to terabytes covering hundreds of topics within the business’s internal and external environment.

Copyright 2017 Cengage Learning. All Rights Reserved. May not be copied, scanned, or duplicated, in whole or in part. Due to electronic rights, some third party content may be suppressed from the eBook and/or eChapter(s).

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4 Part 1 Database Concepts

­ elecommunications companies, such as Sprint and AT&T, are known to have systems T that keep data on trillions of phone calls, with new data being added to the system at speeds up to 70,000 calls per second! Not only do these ­companies have to store and manage immense collections of data, they have to be able to find any given fact in that data quickly. Consider the case of Internet search staple Google. While Google is reluctant to disclose many details about its data storage specifications, it is estimated that the company responds to over 91 million searches per day across a collection of data that is several terabytes in size. Impressively, the results of these searches are available almost instantly.

How can these businesses process this much data? How can they store it all, and then quickly retrieve just the facts that decision makers want to know, just when they want to know it? The answer is that they use databases. Databases, as explained in detail throughout this book, are specialized structures that allow computer-based systems to store, manage, and retrieve data very quickly. Virtually all modern business systems rely on databases. Therefore, a good understanding of how these structures are created and their proper use is vital for any information systems professional. Even if your career does not take you down the amazing path of database design and development, databases will be a key component of the systems that you use. In any case, you will probably make decisions in your career based on information generated from data. Thus, it is important that you know the difference between data and information.

1-2 Data versus Information

data Raw facts, or facts that have not yet been processed to reveal their meaning to the end user.

information The result of processing raw data to reveal its meaning. Information consists of transformed data and facilitates decision making.

To understand what drives database design, you must understand the difference between data and information. Data consists of raw facts. The word raw indicates that the facts have not yet been processed to reveal their meaning. For example, suppose that a university tracks data on faculty members for reporting to accrediting bodies. To get the data for each faculty member into the database, you would provide a screen to allow for convenient data entry, complete with drop-down lists, combo boxes, option buttons, and other data-entry validation controls. Figure 1.2(a) shows a simple data-entry form from a software package named Sedona. When the data is entered into the form and saved, it is placed in the underlying database as raw data, as shown in Figure 1.2(b). Although you now have the facts in hand, they are not particularly useful in this format. Reading through hundreds of rows of data for faculty members does not provide much insight into the overall makeup of the faculty. Therefore, you transform the raw data into a data summary like the one shown in Figure 1.2(c). Now you can get quick answers to questions such as “What percentage of the faculty in the Information Systems (INFS) department are adjuncts?” In this case, you can quickly determine that 20 percent of the INFS faculty members are adjunct faculty. Because graphics can enhance your ability to quickly extract meaning from data, you show the data summary pie chart in Figure 1.2(d).

Information is the result of processing raw data to reveal its meaning. Data processing can be as simple as organizing data to reveal patterns or as complex as making forecasts or drawing inferences using statistical modeling. To reveal meaning, information requires context. For example, an average temperature reading of 105 degrees does not mean much unless you also know its context: Is this reading in degrees Fahrenheit or Celsius? Is this a machine temperature, a body temperature, or an outside air temperature? Information can be used as the foundation for decision making. For example, the data summary for the faculty can provide accrediting bodies with insights that are useful in determining whether to renew accreditation for the university.

Keep in mind that raw data must be properly formatted for storage, processing, and ­presentation. For example, dates might be stored in Julian calendar formats within the database, but displayed in a variety of formats, such as day-month-year or month/day/year, for

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Chapter 1 Database Systems 5

FIGURE 1.2 TRANSFORMING RAW DATA INTO INFORMATION a) Data entry screen

b) Raw data

c) Information in summary format

d) Information in graphical format

different purposes. Respondents’ yes/no responses might need to be converted to a Y/N or 0/1 format for data storage. More complex formatting is required when working with complex data types, such as sounds, videos, or images.

In this “information age,” production of accurate, relevant, and timely information is the key to good decision making. In turn, good decision making is the key to business survival in a global market. We are now said to be entering the “knowledge age.”1 Data is the foundation of ­information, which is the bedrock of knowledge—that is, the body of information and facts about a specific subject. Knowledge implies familiarity, awareness, and understanding of information as it applies to an environment. A key characteristic of knowledge is that “new” knowledge can be derived from “old” knowledge.

Let’s summarize some key points: • Data constitutes the building blocks of information.

• Information is produced by processing data.

• Information is used to reveal the meaning of data.

• Accurate, relevant, and timely information is the key to good decision making.

• Good decision making is the key to organizational survival in a global e­ nvironment.

Peter Drucker coined the phrase “knowledge worker” in 1959 in his book Landmarks of Tomorrow. In 1994, Esther Dyson, George ­Keyworth, and Dr. Alvin Toffler introduced the concept of the “knowledge age.”

1

knowledge The body of information and facts about a specific subject.

Knowledge implies familiarity, awareness, and understanding of information as it applies to an environment. A key characteristic is that new knowledge can be derived from old knowledge.

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6 Part 1 Database Concepts

Timely and useful information requires accurate data. Such data must be p ­ roperly generated and stored in a format that is easy to access and process. In addition, like any basic resource, the data environment must be managed carefully. Data management is a discipline that focuses on the proper generation, storage, and retrieval of data. Given the crucial role that data plays, it should not surprise you that data management is a core activity for any business, government agency, service organization, or charity.

1-3 Introducing the Database Efficient data management typically requires the use of a computer database. A ­database is a shared, integrated computer structure that stores a collection of the following: • End-user data—that is, raw facts of interest to the end user • Metadata, or data about data, through which the end-user data is integrated and ­managed

data management A process that focuses on data collection, storage, and retrieval.

Common data management functions include addition, deletion, modification, and listing.

database A shared, integrated computer structure that houses a collection of related data. A database contains two types of data: end-user data (raw facts) and metadata.

metadata Data about data; that is, data about data characteristics and relationships. See also data dictionary.

database ­management system (DBMS) The collection of programs that manages the database structure and controls access to the data stored in the database.

The metadata describes the data characteristics and the set of relationships that links the data found within the database. For example, the metadata component stores information such as the name of each data element, the type of values (numeric, dates, or text) stored on each data element, and whether the data element can be left empty. The metadata provides information that complements and expands the value and use of the data.

In short, metadata presents a more complete picture of the data in the database. Given the characteristics of metadata, you might hear a database described as a “collection of self-describing data.”

A database management system (DBMS) is a collection of programs that manages the database structure and controls access to the data stored in the database. In a sense, a database resembles a very well-organized electronic filing cabinet in which powerful software (the DBMS) helps manage the cabinet’s contents.

1-3a Role and Advantages of the DBMS The DBMS serves as the intermediary between the user and the database. The database structure itself is stored as a collection of files, and the only way to access the data in those files is through the DBMS. Figure 1.3 emphasizes the point that the DBMS presents the end user (or application program) with a single, integrated view of the data in the database. The DBMS receives all application requests and translates them into the complex operations required to fulfill those requests. The DBMS hides much of the database’s internal complexity from the application programs and users. The application program might be written by a programmer using a ­programming language, such as Visual Basic.

NET, Java, or C#, or it might be created through a DBMS utility program.

Having a DBMS between the end user’s applications and the database offers some important advantages. First, the DBMS enables the data in the database to be shared among multiple applications or users. Second, the DBMS integrates the many different users’ views of the data into a single all-encompassing data r­ epository.

Because data is the crucial raw material from which information is derived, you must have a good method to manage such data. As you will discover in this book, the DBMS helps make data management more efficient and effective. In particular, a DBMS provides these advantages: • Improved data sharing. The DBMS helps create an environment in which end users have better access to more and better-managed data. Such access makes it possible for end users to respond quickly to changes in their environment.

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Chapter 1 Database Systems 7

FIGURE 1.3 THE DBMS MANAGES THE INTERACTION BETWEEN THE END USER AND THE DATABASE End users Database structure

Data

Metadata

Application request

Customers DBMS (Database management system)

http://

Single View of data Integrated

End users Application request

Data

End-user data

Invoices Products

• Improved data security. The more users access the data, the greater the risks of data security breaches. Corporations invest considerable amounts of time, effort, and money to ensure that corporate data is used properly. A DBMS provides a framework for better enforcement of data privacy and security policies.

• Better data integration. Wider access to well-managed data promotes an integrated view of the organization’s operations and a clearer view of the big picture. It becomes much easier to see how actions in one segment of the company affect other segments.

• Minimized data inconsistency. Data inconsistency exists when different versions of the same data appears in different places. For example, data inconsistency exists when a company’s sales department stores a sales representative’s name as Bill Brown and the company’s personnel department stores that same person’s name as William G. Brown, or when the company’s regional sales office shows the price of a product as $45.95 and its national sales office shows the same product’s price as $43.95. The probability of data inconsistency is greatly reduced in a properly designed database.

• Improved data access. The DBMS makes it possible to produce quick answers to ad hoc queries. From a database perspective, a query is a specific request issued to the DBMS for data manipulation—for example, to read or update the data. Simply put, a query is a question, and an ad hoc query is a spur-of-the-moment question. The DBMS sends back an answer (called the query result set) to the application. For example, when dealing with large amounts of sales data, end users might want quick answers to questions (ad hoc queries). Some examples include the following: –– What was the dollar volume of sales by product during the past six months?

–– What is the sales bonus figure for each of our salespeople during the past three months?

–– How many of our customers have credit balances of $3,000 or more?

data inconsistency A condition in which different versions of the same data yield different (inconsistent) results.

query A question or task asked by an end user of a database in the form of SQL code. A specific request for data manipulation issued by the end user or the application to the DBMS.

ad hoc query A “spur-of-the-moment” question.

query result set The collection of data rows returned by a query.

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8 Part 1 Database Concepts

data quality A comprehensive ­approach to ensuring the accuracy, validity, and timeliness of data.

single-user database

• Improved decision making. Better-managed data and improved data access make it possible to generate better-quality information, on which better decisions are based. The quality of the information generated depends on the quality of the ­underlying data. Data quality is a comprehensive approach to promoting the accuracy, validity, and timeliness of the data. While the DBMS does not guarantee data quality, it provides a framework to facilitate data quality initiatives. Data quality concepts will be covered in more detail in Chapter 16, Database Administration and Security.

• Increased end-user productivity. The availability of data, combined with the tools that transform data into usable information, empowers end users to make quick, informed decisions that can make the difference between success and failure in the global economy.

desktop database

The advantages of using a DBMS are not limited to the few just listed. In fact, you will discover many more advantages as you learn more about the technical details of databases and their proper design.

A single-user database that runs on a personal computer.

1-3b Types of Databases

A database that supports only one user at a time.

multiuser database A database that supports multiple concurrent users.

workgroup database A multiuser database that usually supports fewer than 50 users or is used for a specific department in an organization.

enterprise database The overall company data representation, which provides support for present and expected future needs.

centralized database A database located at a single site.

distributed database A logically related database that is stored in two or more physically independent sites.

cloud database A database that is created and maintained using cloud services, such as ­Microsoft Azure or ­Amazon AWS.

general-purpose database A database that contains a wide variety of data used in multiple ­disciplines.

A DBMS can be used to build many different types of databases. Each database stores a particular collection of data and is used for a specific purpose. Over the years, as technology and innovative uses of databases have evolved, different methods have been used to classify databases. For example, databases can be classified by the number of users supported, where the data is located, the type of data stored, the intended data usage, and the degree to which the data is structured.

The number of users determines whether the database is classified as single user or multiuser. A single-user database supports only one user at a time. In other words, if user A is using the database, users B and C must wait until user A is done. A single-user database that runs on a personal computer is called a desktop database. In contrast, a multiuser database supports multiple users at the same time. When the multiuser database supports a relatively small number of users (usually fewer than 50) or a specific department within an organization, it is called a workgroup database. When the database is used by the entire organization and supports many users (more than 50, usually hundreds) across many departments, the database is known as an enterprise database.

Location might also be used to classify the database. For example, a database that supports data located at a single site is called a centralized database. A database that ­supports data distributed across several different sites is called a distributed ­database. The extent to which a database can be distributed and the way in which such distribution is managed are addressed in detail in Chapter 12, Distributed Database ­Management Systems.

Both centralized and decentralized (distributed) databases require a well-defined infrastructure (hardware, operating systems, network technologies, etc.) to implement and operate the database. Typically, the infrastructure is owned and maintained by the organization that creates and operates the database. But in recent years, the use of cloud databases has been growing in popularity. A cloud database is a database that is created and maintained using cloud data services, such as Microsoft Azure or Amazon AWS. These services, provided by third-party vendors, provide defined performance measures (data storage capacity, required throughput, and availability) for the database, but do not necessarily specify the underlying infrastructure to implement it. The data owner does not have to know, or be concerned about, what hardware and software is being used to support their database. The performance capabilities can be renegotiated with the

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Chapter 1 Database Systems 9

cloud provider as the business demands on the database change. For example, during the 2012 presidential election in the United States, the Obama campaign used a cloud database hosted on infrastructure capabilities purchased from Amazon. The campaign did not have to buy, install, configure, or maintain any hardware, operating systems, or network devices. It simply purchased storage and processing capacity for its data and applications. As the demands on the database increased, additional processing and storage capabilities could be purchased as needed.

In some contexts, such as research environments, a popular way of classifying databases is according to the type of data stored in them. Using this criterion, databases are grouped into two categories: general-purpose and discipline-specific databases.

General-purpose databases contain a wide variety of data used in multiple disciplines—for example, a census database that contains general demographic data and the LexisNexis and ProQuest databases that contain newspaper, magazine, and journal articles for a variety of topics. Discipline-specific databases contain data focused on specific subject areas. The data in this type of database is used mainly for academic or research purposes within a small set of disciplines. Examples of discipline-specific databases include financial data stored in databases such as CompuStat or CRSP (Center for Research in Security Prices), geographic information system (GIS) databases that store geospatial and other related data, and medical databases that store confidential ­medical history data.

The most popular way of classifying databases today, however, is based on how they will be used and on the time sensitivity of the information gathered from them.

For example, transactions such as product or service sales, payments, and supply purchases reflect critical day-to-day operations. Such transactions must be recorded accurately and immediately. A database that is designed primarily to support a company’s day-to-day operations is classified as an operational database, also known as an online transaction processing (OLTP) database, transactional database, or production database. In contrast, an analytical database focuses primarily on storing historical data and business metrics used exclusively for tactical or strategic decision making. Such analysis typically requires extensive “data massaging” (data manipulation) to produce information on which to base pricing decisions, sales forecasts, market strategies, and so on. Analytical databases allow the end user to perform advanced analysis of business data using sophisticated tools.

Typically, analytical databases comprise two main components: a data warehouse and an online analytical processing front end. The data warehouse is a specialized database that stores data in a format optimized for decision support. The data warehouse contains historical data obtained from the operational databases as well as data from other external sources. Online analytical processing (OLAP) is a set of tools that work together to provide an advanced data analysis environment for retrieving, processing, and modeling data from the data warehouse. In recent times, this area of database application has grown in importance and usage, to the point that it has evolved into its own discipline: business intelligence. The term business intelligence describes a comprehensive approach to capture and process business data with the purpose of generating information to support business decision making. Chapter 13, Business Intelligence and Data Warehouses, covers this topic in detail.

Databases can also be classified to reflect the degree to which the data is structured.

Unstructured data is data that exists in its original (raw) state—that is, in the format in which it was collected. Therefore, unstructured data exists in a format that does not lend itself to the processing that yields information. Structured data is the result of formatting unstructured data to facilitate storage, use, and the generation of information.

You apply structure (format) based on the type of processing that you intend to perform

discipline-specific ­database A database that contains data focused on specific subject areas.

operational ­database A database designed primarily to support a company’s day-to-day operations. Also known as a transactional database, OLTP database, or production database.

online transaction ­processing (OLTP) ­database See operational database.

transactional ­database See operational database.

production database See operational database.

analytical database A database focused primarily on storing ­historical data and business metrics used for tactical or strategic decision making.

data warehouse A specialized database that stores historical and aggregated data in a format optimized for decision support.

online analytical processing (OLAP) A set of tools that provide advanced data analysis for retrieving, processing, and modeling data from the data warehouse.

business intelligence A set of tools and processes used to capture, collect, integrate, store, and analyze data to support business decision making.

unstructured data Data that exists in its original, raw state; that is, in the format in which it was collected.

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DANCE ON STILTS AT THE GIRLS’ UNYAGO, NIUCHI

Newala, too, suffers from the distance of its water-supply—at least the Newala of to-day does; there was once another Newala in a lovely valley at the foot of the plateau. I visited it and found scarcely a trace of houses, only a Christian cemetery, with the graves of several missionaries and their converts, remaining as a monument of its former glories. But the surroundings are wonderfully beautiful. A thick grove of splendid mango-trees closes in the weather-worn crosses and headstones; behind them, combining the useful and the agreeable, is a whole plantation of lemon-trees covered with ripe fruit; not the small African kind, but a much larger and also juicier imported variety, which drops into the hands of the passing traveller, without calling for any exertion on his part. Old Newala is now under the jurisdiction of the native pastor, Daudi, at Chingulungulu, who, as I am on very friendly terms with him, allows me, as a matter of course, the use of this lemon-grove during my stay at Newala.

FEET MUTILATED BY THE RAVAGES OF THE “JIGGER” (Sarcopsylla penetrans)

The water-supply of New Newala is in the bottom of the valley, some 1,600 feet lower down. The way is not only long and fatiguing, but the water, when we get it, is thoroughly bad. We are suffering not only from this, but from the fact that the arrangements at Newala are nothing short of luxurious. We have a separate kitchen—a hut built against the boma palisade on the right of the baraza, the interior of which is not visible from our usual position. Our two cooks were not long in finding this out, and they consequently do—or rather neglect to do—what they please. In any case they do not seem to be very particular about the boiling of our drinking-water—at least I can attribute to no other cause certain attacks of a dysenteric nature, from which both Knudsen and I have suffered for some time. If a man like Omari has to be left unwatched for a moment, he is capable of anything. Besides this complaint, we are inconvenienced by the state of our nails, which have become as hard as glass, and crack on the slightest provocation, and I have the additional infliction of pimples all over me. As if all this were not enough, we have also, for the last week been waging war against the jigger, who has found his Eldorado in the hot sand of the Makonde plateau. Our men are seen all day long—whenever their chronic colds and the dysentery likewise raging among them permit—occupied in removing this scourge of Africa from their feet and trying to prevent the disastrous consequences of its presence. It is quite common to see natives of this place with one or two toes missing; many have lost all their toes,

or even the whole front part of the foot, so that a well-formed leg ends in a shapeless stump. These ravages are caused by the female of Sarcopsylla penetrans, which bores its way under the skin and there develops an egg-sac the size of a pea. In all books on the subject, it is stated that one’s attention is called to the presence of this parasite by an intolerable itching. This agrees very well with my experience, so far as the softer parts of the sole, the spaces between and under the toes, and the side of the foot are concerned, but if the creature penetrates through the harder parts of the heel or ball of the foot, it may escape even the most careful search till it has reached maturity.

Then there is no time to be lost, if the horrible ulceration, of which we see cases by the dozen every day, is to be prevented. It is much easier, by the way, to discover the insect on the white skin of a European than on that of a native, on which the dark speck scarcely shows. The four or five jiggers which, in spite of the fact that I constantly wore high laced boots, chose my feet to settle in, were taken out for me by the all-accomplished Knudsen, after which I thought it advisable to wash out the cavities with corrosive sublimate. The natives have a different sort of disinfectant—they fill the hole with scraped roots. In a tiny Makua village on the slope of the plateau south of Newala, we saw an old woman who had filled all the spaces under her toe-nails with powdered roots by way of prophylactic treatment. What will be the result, if any, who can say?

The rest of the many trifling ills which trouble our existence are really more comic than serious. In the absence of anything else to smoke, Knudsen and I at last opened a box of cigars procured from the Indian store-keeper at Lindi, and tried them, with the most distressing results. Whether they contain opium or some other narcotic, neither of us can say, but after the tenth puff we were both “off,” three-quarters stupefied and unspeakably wretched. Slowly we recovered—and what happened next? Half-an-hour later we were once more smoking these poisonous concoctions—so insatiable is the craving for tobacco in the tropics.

Even my present attacks of fever scarcely deserve to be taken seriously. I have had no less than three here at Newala, all of which have run their course in an incredibly short time. In the early afternoon, I am busy with my old natives, asking questions and making notes. The strong midday coffee has stimulated my spirits to

an extraordinary degree, the brain is active and vigorous, and work progresses rapidly, while a pleasant warmth pervades the whole body. Suddenly this gives place to a violent chill, forcing me to put on my overcoat, though it is only half-past three and the afternoon sun is at its hottest. Now the brain no longer works with such acuteness and logical precision; more especially does it fail me in trying to establish the syntax of the difficult Makua language on which I have ventured, as if I had not enough to do without it. Under the circumstances it seems advisable to take my temperature, and I do so, to save trouble, without leaving my seat, and while going on with my work. On examination, I find it to be 101·48°. My tutors are abruptly dismissed and my bed set up in the baraza; a few minutes later I am in it and treating myself internally with hot water and lemon-juice.

Three hours later, the thermometer marks nearly 104°, and I make them carry me back into the tent, bed and all, as I am now perspiring heavily, and exposure to the cold wind just beginning to blow might mean a fatal chill. I lie still for a little while, and then find, to my great relief, that the temperature is not rising, but rather falling. This is about 7.30 p.m. At 8 p.m. I find, to my unbounded astonishment, that it has fallen below 98·6°, and I feel perfectly well. I read for an hour or two, and could very well enjoy a smoke, if I had the wherewithal—Indian cigars being out of the question.

Having no medical training, I am at a loss to account for this state of things. It is impossible that these transitory attacks of high fever should be malarial; it seems more probable that they are due to a kind of sunstroke. On consulting my note-book, I become more and more inclined to think this is the case, for these attacks regularly follow extreme fatigue and long exposure to strong sunshine. They at least have the advantage of being only short interruptions to my work, as on the following morning I am always quite fresh and fit.

My treasure of a cook is suffering from an enormous hydrocele which makes it difficult for him to get up, and Moritz is obliged to keep in the dark on account of his inflamed eyes. Knudsen’s cook, a raw boy from somewhere in the bush, knows still less of cooking than Omari; consequently Nils Knudsen himself has been promoted to the vacant post. Finding that we had come to the end of our supplies, he began by sending to Chingulungulu for the four sucking-pigs which we had

bought from Matola and temporarily left in his charge; and when they came up, neatly packed in a large crate, he callously slaughtered the biggest of them. The first joint we were thoughtless enough to entrust for roasting to Knudsen’s mshenzi cook, and it was consequently uneatable; but we made the rest of the animal into a jelly which we ate with great relish after weeks of underfeeding, consuming incredible helpings of it at both midday and evening meals. The only drawback is a certain want of variety in the tinned vegetables. Dr. Jäger, to whom the Geographical Commission entrusted the provisioning of the expeditions—mine as well as his own—because he had more time on his hands than the rest of us, seems to have laid in a huge stock of Teltow turnips,[46] an article of food which is all very well for occasional use, but which quickly palls when set before one every day; and we seem to have no other tins left. There is no help for it—we must put up with the turnips; but I am certain that, once I am home again, I shall not touch them for ten years to come.

Amid all these minor evils, which, after all, go to make up the genuine flavour of Africa, there is at least one cheering touch: Knudsen has, with the dexterity of a skilled mechanic, repaired my 9 × 12 cm. camera, at least so far that I can use it with a little care.

How, in the absence of finger-nails, he was able to accomplish such a ticklish piece of work, having no tool but a clumsy screw-driver for taking to pieces and putting together again the complicated mechanism of the instantaneous shutter, is still a mystery to me; but he did it successfully. The loss of his finger-nails shows him in a light contrasting curiously enough with the intelligence evinced by the above operation; though, after all, it is scarcely surprising after his ten years’ residence in the bush. One day, at Lindi, he had occasion to wash a dog, which must have been in need of very thorough cleansing, for the bottle handed to our friend for the purpose had an extremely strong smell. Having performed his task in the most conscientious manner, he perceived with some surprise that the dog did not appear much the better for it, and was further surprised by finding his own nails ulcerating away in the course of the next few days. “How was I to know that carbolic acid has to be diluted?” he mutters indignantly, from time to time, with a troubled gaze at his mutilated finger-tips.

Since we came to Newala we have been making excursions in all directions through the surrounding country, in accordance with old habit, and also because the akida Sefu did not get together the tribal elders from whom I wanted information so speedily as he had promised. There is, however, no harm done, as, even if seen only from the outside, the country and people are interesting enough.

The Makonde plateau is like a large rectangular table rounded off at the corners. Measured from the Indian Ocean to Newala, it is about seventy-five miles long, and between the Rovuma and the Lukuledi it averages fifty miles in breadth, so that its superficial area is about two-thirds of that of the kingdom of Saxony. The surface, however, is not level, but uniformly inclined from its south-western edge to the ocean. From the upper edge, on which Newala lies, the eye ranges for many miles east and north-east, without encountering any obstacle, over the Makonde bush. It is a green sea, from which here and there thick clouds of smoke rise, to show that it, too, is inhabited by men who carry on their tillage like so many other primitive peoples, by cutting down and burning the bush, and manuring with the ashes. Even in the radiant light of a tropical day such a fire is a grand sight.

Much less effective is the impression produced just now by the great western plain as seen from the edge of the plateau. As often as time permits, I stroll along this edge, sometimes in one direction, sometimes in another, in the hope of finding the air clear enough to let me enjoy the view; but I have always been disappointed.

Wherever one looks, clouds of smoke rise from the burning bush, and the air is full of smoke and vapour. It is a pity, for under more favourable circumstances the panorama of the whole country up to the distant Majeje hills must be truly magnificent. It is of little use taking photographs now, and an outline sketch gives a very poor idea of the scenery. In one of these excursions I went out of my way to make a personal attempt on the Makonde bush. The present edge of the plateau is the result of a far-reaching process of destruction through erosion and denudation. The Makonde strata are everywhere cut into by ravines, which, though short, are hundreds of yards in depth. In consequence of the loose stratification of these beds, not only are the walls of these ravines nearly vertical, but their upper end is closed by an equally steep escarpment, so that the

western edge of the Makonde plateau is hemmed in by a series of deep, basin-like valleys. In order to get from one side of such a ravine to the other, I cut my way through the bush with a dozen of my men.

It was a very open part, with more grass than scrub, but even so the short stretch of less than two hundred yards was very hard work; at the end of it the men’s calicoes were in rags and they themselves bleeding from hundreds of scratches, while even our strong khaki suits had not escaped scatheless.

NATIVE PATH THROUGH THE MAKONDE BUSH, NEAR MAHUTA

I see increasing reason to believe that the view formed some time back as to the origin of the Makonde bush is the correct one. I have no doubt that it is not a natural product, but the result of human occupation. Those parts of the high country where man—as a very slight amount of practice enables the eye to perceive at once—has not yet penetrated with axe and hoe, are still occupied by a splendid timber forest quite able to sustain a comparison with our mixed forests in Germany. But wherever man has once built his hut or tilled his field, this horrible bush springs up. Every phase of this process

may be seen in the course of a couple of hours’ walk along the main road. From the bush to right or left, one hears the sound of the axe— not from one spot only, but from several directions at once. A few steps further on, we can see what is taking place. The brush has been cut down and piled up in heaps to the height of a yard or more, between which the trunks of the large trees stand up like the last pillars of a magnificent ruined building. These, too, present a melancholy spectacle: the destructive Makonde have ringed them— cut a broad strip of bark all round to ensure their dying off—and also piled up pyramids of brush round them. Father and son, mother and son-in-law, are chopping away perseveringly in the background—too busy, almost, to look round at the white stranger, who usually excites so much interest. If you pass by the same place a week later, the piles of brushwood have disappeared and a thick layer of ashes has taken the place of the green forest. The large trees stretch their smouldering trunks and branches in dumb accusation to heaven—if they have not already fallen and been more or less reduced to ashes, perhaps only showing as a white stripe on the dark ground.

This work of destruction is carried out by the Makonde alike on the virgin forest and on the bush which has sprung up on sites already cultivated and deserted. In the second case they are saved the trouble of burning the large trees, these being entirely absent in the secondary bush.

After burning this piece of forest ground and loosening it with the hoe, the native sows his corn and plants his vegetables. All over the country, he goes in for bed-culture, which requires, and, in fact, receives, the most careful attention. Weeds are nowhere tolerated in the south of German East Africa. The crops may fail on the plains, where droughts are frequent, but never on the plateau with its abundant rains and heavy dews. Its fortunate inhabitants even have the satisfaction of seeing the proud Wayao and Wamakua working for them as labourers, driven by hunger to serve where they were accustomed to rule.

But the light, sandy soil is soon exhausted, and would yield no harvest the second year if cultivated twice running. This fact has been familiar to the native for ages; consequently he provides in time, and, while his crop is growing, prepares the next plot with axe and firebrand. Next year he plants this with his various crops and

lets the first piece lie fallow. For a short time it remains waste and desolate; then nature steps in to repair the destruction wrought by man; a thousand new growths spring out of the exhausted soil, and even the old stumps put forth fresh shoots. Next year the new growth is up to one’s knees, and in a few years more it is that terrible, impenetrable bush, which maintains its position till the black occupier of the land has made the round of all the available sites and come back to his starting point.

The Makonde are, body and soul, so to speak, one with this bush.

According to my Yao informants, indeed, their name means nothing else but “bush people.” Their own tradition says that they have been settled up here for a very long time, but to my surprise they laid great stress on an original immigration. Their old homes were in the south-east, near Mikindani and the mouth of the Rovuma, whence their peaceful forefathers were driven by the continual raids of the Sakalavas from Madagascar and the warlike Shirazis[47] of the coast, to take refuge on the almost inaccessible plateau. I have studied African ethnology for twenty years, but the fact that changes of population in this apparently quiet and peaceable corner of the earth could have been occasioned by outside enterprises taking place on the high seas, was completely new to me. It is, no doubt, however, correct.

The charming tribal legend of the Makonde—besides informing us of other interesting matters—explains why they have to live in the thickest of the bush and a long way from the edge of the plateau, instead of making their permanent homes beside the purling brooks and springs of the low country.

“The place where the tribe originated is Mahuta, on the southern side of the plateau towards the Rovuma, where of old time there was nothing but thick bush. Out of this bush came a man who never washed himself or shaved his head, and who ate and drank but little.

He went out and made a human figure from the wood of a tree growing in the open country, which he took home to his abode in the bush and there set it upright. In the night this image came to life and was a woman. The man and woman went down together to the Rovuma to wash themselves. Here the woman gave birth to a stillborn child. They left that place and passed over the high land into the valley of the Mbemkuru, where the woman had another child, which

was also born dead. Then they returned to the high bush country of Mahuta, where the third child was born, which lived and grew up. In course of time, the couple had many more children, and called themselves Wamatanda. These were the ancestral stock of the Makonde, also called Wamakonde,[48] i.e., aborigines. Their forefather, the man from the bush, gave his children the command to bury their dead upright, in memory of the mother of their race who was cut out of wood and awoke to life when standing upright. He also warned them against settling in the valleys and near large streams, for sickness and death dwelt there. They were to make it a rule to have their huts at least an hour’s walk from the nearest wateringplace; then their children would thrive and escape illness.”

The explanation of the name Makonde given by my informants is somewhat different from that contained in the above legend, which I extract from a little book (small, but packed with information), by Pater Adams, entitled Lindi und sein Hinterland. Otherwise, my results agree exactly with the statements of the legend. Washing?

Hapana—there is no such thing. Why should they do so? As it is, the supply of water scarcely suffices for cooking and drinking; other people do not wash, so why should the Makonde distinguish himself by such needless eccentricity? As for shaving the head, the short, woolly crop scarcely needs it,[49] so the second ancestral precept is likewise easy enough to follow. Beyond this, however, there is nothing ridiculous in the ancestor’s advice. I have obtained from various local artists a fairly large number of figures carved in wood, ranging from fifteen to twenty-three inches in height, and representing women belonging to the great group of the Mavia, Makonde, and Matambwe tribes. The carving is remarkably well done and renders the female type with great accuracy, especially the keloid ornamentation, to be described later on. As to the object and meaning of their works the sculptors either could or (more probably) would tell me nothing, and I was forced to content myself with the scanty information vouchsafed by one man, who said that the figures were merely intended to represent the nembo—the artificial deformations of pelele, ear-discs, and keloids. The legend recorded

by Pater Adams places these figures in a new light. They must surely be more than mere dolls; and we may even venture to assume that they are—though the majority of present-day Makonde are probably unaware of the fact—representations of the tribal ancestress.

The references in the legend to the descent from Mahuta to the Rovuma, and to a journey across the highlands into the Mbekuru valley, undoubtedly indicate the previous history of the tribe, the travels of the ancestral pair typifying the migrations of their descendants. The descent to the neighbouring Rovuma valley, with its extraordinary fertility and great abundance of game, is intelligible at a glance—but the crossing of the Lukuledi depression, the ascent to the Rondo Plateau and the descent to the Mbemkuru, also lie within the bounds of probability, for all these districts have exactly the same character as the extreme south. Now, however, comes a point of especial interest for our bacteriological age. The primitive Makonde did not enjoy their lives in the marshy river-valleys.

Disease raged among them, and many died. It was only after they had returned to their original home near Mahuta, that the health conditions of these people improved. We are very apt to think of the African as a stupid person whose ignorance of nature is only equalled by his fear of it, and who looks on all mishaps as caused by evil spirits and malignant natural powers. It is much more correct to assume in this case that the people very early learnt to distinguish districts infested with malaria from those where it is absent.

This knowledge is crystallized in the ancestral warning against settling in the valleys and near the great waters, the dwelling-places of disease and death. At the same time, for security against the hostile Mavia south of the Rovuma, it was enacted that every settlement must be not less than a certain distance from the southern edge of the plateau. Such in fact is their mode of life at the present day. It is not such a bad one, and certainly they are both safer and more comfortable than the Makua, the recent intruders from the south, who have made USUAL METHOD OF good their footing on the western edge of the CLOSING HUT-DOOR plateau, extending over a fairly wide belt of country. Neither Makua nor Makonde show in their dwellings anything of the size and comeliness of the Yao houses in the plain, especially at Masasi, Chingulungulu and Zuza’s. Jumbe Chauro, a Makonde hamlet not far from Newala, on the road to Mahuta, is the

most important settlement of the tribe I have yet seen, and has fairly spacious huts. But how slovenly is their construction compared with the palatial residences of the elephant-hunters living in the plain.

The roofs are still more untidy than in the general run of huts during the dry season, the walls show here and there the scanty beginnings or the lamentable remains of the mud plastering, and the interior is a veritable dog-kennel; dirt, dust and disorder everywhere. A few huts only show any attempt at division into rooms, and this consists merely of very roughly-made bamboo partitions. In one point alone have I noticed any indication of progress—in the method of fastening the door. Houses all over the south are secured in a simple but ingenious manner. The door consists of a set of stout pieces of wood or bamboo, tied with bark-string to two cross-pieces, and moving in two grooves round one of the door-posts, so as to open inwards. If the owner wishes to leave home, he takes two logs as thick as a man’s upper arm and about a yard long. One of these is placed obliquely against the middle of the door from the inside, so as to form an angle of from 60° to 75° with the ground. He then places the second piece horizontally across the first, pressing it downward with all his might.

It is kept in place by two strong posts planted in the ground a few inches inside the door. This fastening is absolutely safe, but of course cannot be applied to both doors at once, otherwise how could the owner leave or enter his house? I have not yet succeeded in finding out how the back door is fastened.

MAKONDE LOCK AND KEY AT JUMBE CHAURO

This is the general way of closing a house. The Makonde at Jumbe Chauro, however, have a much more complicated, solid and original one. Here, too, the door is as already described, except that there is only one post on the inside, standing by itself about six inches from one side of the doorway. Opposite this post is a hole in the wall just large enough to admit a man’s arm. The door is closed inside by a large wooden bolt passing through a hole in this post and pressing with its free end against the door. The other end has three holes into which fit three pegs running in vertical grooves inside the post. The door is opened with a wooden key about a foot long, somewhat curved and sloped off at the butt; the other end has three pegs corresponding to the holes, in the bolt, so that, when it is thrust through the hole in the wall and inserted into the rectangular opening in the post, the pegs can be lifted and the bolt drawn out.[50]

MODE OF INSERTING THE KEY

With no small pride first one householder and then a second showed me on the spot the action of this greatest invention of the Makonde Highlands. To both with an admiring exclamation of “Vizuri sana!” (“Very fine!”). I expressed the wish to take back these marvels with me to Ulaya, to show the Wazungu what clever fellows the Makonde are. Scarcely five minutes after my return to camp at Newala, the two men came up sweating under the weight of two heavy logs which they laid down at my feet, handing over at the same time the keys of the fallen fortress. Arguing, logically enough, that if the key was wanted, the lock would be wanted with it, they had taken their axes and chopped down the posts—as it never occurred to them to dig them out of the ground and so bring them intact. Thus I have

two badly damaged specimens, and the owners, instead of praise, come in for a blowing-up.

The Makua huts in the environs of Newala are especially miserable; their more than slovenly construction reminds one of the temporary erections of the Makua at Hatia’s, though the people here have not been concerned in a war. It must therefore be due to congenital idleness, or else to the absence of a powerful chief. Even the baraza at Mlipa’s, a short hour’s walk south-east of Newala, shares in this general neglect. While public buildings in this country are usually looked after more or less carefully, this is in evident danger of being blown over by the first strong easterly gale. The only attractive object in this whole district is the grave of the late chief Mlipa. I visited it in the morning, while the sun was still trying with partial success to break through the rolling mists, and the circular grove of tall euphorbias, which, with a broken pot, is all that marks the old king’s resting-place, impressed one with a touch of pathos.

Even my very materially-minded carriers seemed to feel something of the sort, for instead of their usual ribald songs, they chanted solemnly, as we marched on through the dense green of the Makonde bush:—