SAS Data Integration Studio: Fast Track

Overview of SAS Data Integration Data integration is the process of consolidating data from a variety of sources in order to produce a unified view of the data. SAS supports data integration .

SAS Support Data Integration For – SAS integration techniques provide interface that provides interface and enables you to connecting the SAS metadata server i.e. known as IOM server. It also provides java 0bject interface to the metadata and success the functionality. SAS metadata provides the information to data sources. SAS enables you to connect, store, and variety of data stores, streams, applications and systems.

Ex: you can manage info in ERP, messages queues, relational databases, Xml and flat files.

SAS data integrated software enables you to profile, cleanse, augment, and monitor data to create consistent, reliable information. It provides a number of transformations and functions that can be improve the satisfactory of your data. SAS data integration provides interface that access the designers to build the flows and quickly identify the input and output.

SAS data integration creates the view of enterprise data from multiple sources.

Advantage It manages the costs of data by support collaboration, code reuse, and common metadata.

It reduces the development time by enables the rapid generation of data warehouses, data marts, and data streams.

Data integration creates process flows that are reusable, easily modified, and have embedded data quality processing.

SAS Integration Environment SAS describes the Metadata Server as a centralized resource pool for storing metadata for SAS applications and other servers. The Metadata Server is the foundation; without it the whole system is non-functioning. It enables centralized control so that all users access consistent and accurate metadata.

One Metadata Server works with all SAS applications in the environment, supporting hundreds of concurrent users. This architecture enables the following: a) Exchange of metadata between applications, enabling collaboration. b) Centralized management of metadata resources.

Because of a common framework for creating, accessing, and updating metadata, it is easier to manage applications relying on it.

SAS Metadata Server stores information about: a) Enterprise data sources and data structures which are accessed by SAS applications. b) Resources created and used by SAS applications including: report definitions, Stored Process definitions, and scheduled jobs. c) Servers that run SAS processes. d) Users, and groups of users, who use the system, and the levels of access that users and groups have to resources.

SAS Data Integration Studio SAS Data Integration Studio is a visual design tool for building, implementing and managing data integration processes regardless of data sources, applications, or platforms. Through its metadata, SAS Data Integration Studio provides a single point of control for managing. in some cases it can be challenging for a traditional programmer to start development with Data Integration Studio. The leap to use readymade functionalities may feel sizable, especially when manual coding is strongly accustomed to. The sentiment shared often reflects the question: “Why drag and drop boxes trying to “develop” code, instead of just coding it?”

Therefore the first change one will make is the adjustment of one’s stance on accepting and using the new tool. This will be aided by informing the work force about the benefits of the change.

SAS Data integration studio managing the following resources:

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data sources, from any platform that is accessible to SAS and from any format that is accessible to SAS data targets, to any platform that is accessible to SAS, and to any format that is supported

by SAS processes that specify how data is extracted, transformed, and loaded from a source to a target jobs that organize a set of sources, targets, and processes (transformations) source code that is generated by SAS Data Integration Studio user-written source code.

Transformations: The actual development work is started with the transformations. There is a larger variety of transformations in Data Integration Studio as illustrated here in the Figure above. Access and analysis transformations are there for self-explanatory reasons, as well as control, data and quality transformations. In addition to the more traditional ETL transformations, some newer transformations are in place, such as Hadoop and High Performance Analytics transformations. Data can be handled via SQL transformations and pushed into the database or manipulated as was performed in Base SAS, using the User Written transformation. Starting with the Workflow: The training for DIS is usually targeting for the Starting with the Workflow: The training for DIS is usually targeting for the development to take place backwards, starting with the target. When the metadata of the target table 24 Figure 12: Workflow Example - Source Tables is created (and the source table is put in place), the developer starts working on the intermediary transformations. However, usually in practical solutions, the developer or designer does not have the end result clearly defined and will start the software development from the beginning.

SAS Management Console SAS Management Console provides a single interface through which administrators can explore and manage metadata repositories. With this interface, administrators can efficiently set up system resources, manage user and group accounts, and administer security.

SAS certified Data integration Developer skills 

Defining architecture of the platform for SAS Business Analytics.

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Creating metadata for source and target data.

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Creating metadata for target data and jobs.

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Working with transformations.

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Working with tables and table loader transformation.

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Working with slowly changing dimensions.

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Defining generated transformations.

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Deploying jobs

SAS Data integration Certification Requirements The Data Integration Developer works with data to prepare it for analysis and reporting.

Candidates must know how to define the platform architecture for SAS Business Analytics as well as create metadata, transform data and tables, and run jobs. The certification exam features 76 multiple-choice questions, a 105-minute time limit, and candidates must answer at least 70 percent of the questions correctly to pass the exam.

SAS A00-260 Certification Exam Syllabus The SAS Certified Data Integration Developer for SAS 9 credential is globally recognized for validating SAS Data Integration Developer knowledge. With the SAS Certified Data Integration Developer Certification credential, you stand out in a crowd and prove that you have the SAS Data Integration Developer knowledge to make a difference within your organization. The SAS Certified Data Integration Developer for SAS 9 Certification (A00-260) exam will test the candidate's knowledge on following areas.