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From the Excel you know to the Excel you don’t! Microsoft Business Intelligence Discovery Session

Amber McCormack Marketing Executive amber.maccormack@contentandcode.com


Welcome We appreciate your feedback Welcome


From the Excel you know to the Excel you don’t! Microsoft Business Intelligence Discovery Session

Ian Macdonald & Jes Kirkup BI Practice Lead Senior BI Consultant Ian.macdonald@contentandcode.com jeremy.kirkup@contentandcode.com


The Day • 09.30 - Business Intelligence Overview – The big picture

• 10.15 - The Knowledge Workers Perspective – Fact based decision making

• 11.00 - Break • 11.20 - IT and Data Management – Making sure it is right

• 12.00 - The Analyst – Deep dive discovery

• 12.45 – Summary and Next Steps


Content and Code and me Why are we here?

 Content and Code  10 years building information solutions for clients  Best in the world twice and top UK partner

 Me & Jes  25 + 10 years designing, developing, managing and marketing Business Intelligence technologies and solutions  Leading process oriented BI at Content and Code


Setting the Scene • • • • •

Your name Your role Your business pain What you need to help you overcome that pain What does “Business Intelligence” mean to you?


A Question: • Who here is comfortable with the concepts of: – – – – – – – –

• ?

Data Warehouse and Data Marts Master Data Management ETL Dimensions and Facts OLAP, Cubes and UDM Data Mining KPIs Scorecards and Dashboards


The Big Picture of Business Intelligence Goals, Concepts, and the Platform


Business Intelligence BI - Improving Business Insight

“A broad category of applications and technologies for gathering, storing, analysing, sharing and providing access to data to help enterprise users make better business decisions.� Gartner Group


demos 1.

Business Intelligence and Power of Visualisation Balanced Scorecards

Objective: Performance at a glance Complex information made easy to understand


demos What did we see? Visualisations making information come alive Easy to use, intuitive, relevant metrics across my business view As much or little detail as needed


Business Intelligence Today Low end-user adoption rates and high reliance on IT

• Analyst Issues: – Hard to access organisational data – Reliant on IT for reporting – Difficult to share insight

• IT Pro Issues: – No time for ad-hoc BI requests – Lack of control – Organisational BI often expensive


From Organisational BI to Personal BI Enabling managed self-service BI

Empowered, Managed, Accurate

IT Involvement

IT Unmanaged

IT Managed

Corporate BI

Data Data BI and Portals and Sources Marts LOB Apps Dashboards

Accurate Secure Scalable Up to date

Self Service Easy to use On and Offline Collaborative

Rogue “Spreadmarts”

User Context Reliant on IT

Empowered


Microsoft BI Strategy Democratising Business Intelligence

• Familiar environment • Integrated into Microsoft Office • Built on SQL Server Improving organisations by providing business insights to all employees leading to better, faster, more relevant decisions


Complementary BI Contexts

Personal BI Self-Service Ad-hoc Analysis

Team BI Shared, Collaborative Insight

Organisational BI Pre-designed, aligned, approved


Microsoft Business Intelligence You may already have these products Business User Experience

Business Collaboration Platform

Data Infrastructure & BI Platform

Familiar User Experience Self-Service access & insight Data exploration & analysis Integrated Content and Predictive analysis Collaboration Data visualisation Thin client experience Contextual visualisation Dashboards & Scorecards Data SearchInfrastructure and BI Platform Content Management Analysis Services Compositions Reporting Services Integration Services Master Data Services Data Mining Data Warehousing


Complementary BI Technologies

Personal BI PowerPivot for Excel 2010

Team BI PowerPivot for SharePoint 2010 & PerformancePoint Services

Organisational BI SQL Server 2008 R2


Fundamental Concepts


Enterprise Data


Silo Integration Challenge Call Center Web Apps

CRM

SOA – Enterprise Service Bus

Finance

Inventory

Data Warehouse

HR

ERP


Source Systems • Process real-time transactions • Optimised for data modifications – Normalised

• Limited decision support • Commonly called: – Online transaction processing (OLTP) systems – Operational systems HR

Finance

Inventory


Data Warehouse • Provides data for business analysis – Grouped in subject-specific stores called Data Marts

• Optimised for rapid ad-hoc information retrieval • Integrates heterogeneous source systems • Consistent historical data store


ETL: Extract, Transform, and Load 1. Extract data from the source systems 2. Transform data into desired form 3. Load data into the warehouse

ETL


Dimensions and Facts Basis of All BI

• Fact – something that happened – – – –

Sale, purchase, shipping... Transaction or an event Verb Essentially a Measure

• Dimension – describes a fact – Customer, product, account... – Object – Noun

• A fact (measure) is expressed in terms of dimensions – 42 footballs sold to John on 20100115.


Dimensions • Describe business entities • Contain attributes that provide context to numerical data • Present data organised into hierarchies


Predictive Analysis Role of Software Proactive

Data mining

Predictive Analysis Self-service Analysis Interactive OLAP

Ad-hoc reporting

Canned reporting Passive

Business Insight Presentation

Exploration

Discovery


OLAP or Multidimensional Data • Online Analytical Processing = Multidimensional Data • Measures and Dimensions • Uses a calculation engine for fast, flexible transformation of base data (such as aggregates) • Supports discovery of business trends and statistics not directly visible in data warehouse queries


Cube (UDM) Unified Dimensional Model • Combination of measures (from facts) and dimensions as one conceptual model • Rich data model enhanced by – – – – – –

Calculations Key Performance Indicators (KPIs) Actions Perspectives Translations Partitions

• Formally, cube is called a UDM


Cube Products

Cars Parts Accessories 2009 Q1

Dates

Jan Feb

Mar

Measures


Dicing a Cube Products

Cars Parts Accessories 2009

Dates

Measures

25

Q1

6

Jan

2

Feb

3

Mar

1


Ad-hoc Self-Service Analysis • Interactive, pivot-based analysis of column-oriented large volumes of data (>>millions of rows) • Pivots, advanced filtering (slicers), and tabular expressions + • OLAP-style analytics – Almost multidimensional – “Cubes without a cube in Excel”


Data Mining • Discovery of (very) hidden patterns in mountains of data • Correlation search engine • Combination of statistics, probability analysis, database technologies, machine learning, and AI


Key Performance Indicator (KPI) • Measurement comparing performance to goals • Grouped into a business scorecard to show company health – Ideally, with a balanced perspective onto groups of KPIs

• Built with: – Using OLAP (enterprise-level KPIs) – In SharePoint Server PerformancePoint Services (often team KPIs) – Using data mining (predictive KPI)


KPI Characteristics • • • •

Value Goal Status Trend


Dashboards and Scorecards • Scorecard – Table (pivot-like) of KPIs

• Dashboard – Contains scorecards, analytical reports, and other analytical visualisations

• Create them: – DIY: PowerPivot – Quickly: SharePoint 2010 PerformancePoint Services – Bespoke: custom SharePoint, Silverlight, and .NET development


Conclusions


Š 2010 Microsoft Corporation & Content and Code Ltd. All rights reserved. The information herein is for informational purposes only and represents the opinions and views of Content and Code. The material presented is not certain and may vary based on several factors. Microsoft makes no warranties, express, implied or statutory, as to the information in this presentation. Š 2010 Microsoft Corp. Some slides contain quotations from copyrighted materials by other authors, as individually attributed or as already covered by Microsoft Copyright ownerships. All rights reserved. Microsoft, Windows, Windows Vista and other product names are or may be registered trademarks and/or trademarks in the U.S. and/or other countries. The information herein is for informational purposes only and represents the current view of Content and Code as of the date of this presentation. Because Content and Code & Microsoft must respond to changing market conditions, it should not be interpreted to be a commitment on the part of Microsoft, and Microsoft and Content and Code cannot guarantee the accuracy of any information provided after the date of this presentation. Content and Code no warranties, express, implied or statutory, as to the information in this presentation. E&OE.


The Big Picture of Business Intelligence