All you need to know about Microsoft Business Intelligence - 4 video sessions

Rafal Lukawiecki  live at the Stockholm Business Intelligence Conference April 21 2009

Rafal Lukawiecki presents how Microsoft Business Intelligence can be used in a number of different senarios.

He shows overall BI strategy, demos and customer cases at the Business Intelligence Conference in Stockholm.

If you see all four sessions you will have a good overview of what is possible to do with Microsoft Business Intelligence, Office 2007, SharePoint 2007 and SQL Server 2008.

Session 1

• Introductions and Overview of Seminar
• Session 1 Intro: Improving Insight and Decision Making Using Microsoft Business Intelligence and SQL Server 2008
• What is Performance Management in BI?
• Demo: BI in an Enterprise (Dashboards, Scorecards, KPIs, Analytic Charts, Strategy Maps, Performance Maps, Decomposition Trees, BI Collaboration)
• Landscape of Microsoft BI
• Microsoft BI Technology Platform
• Fundamental Concepts: Evolution from Transactions to BI
• Transactional Source System Characteristics
• Data Warehouse Characteristics
• Facts and Dimensions Defined
• Predictive Analytics
• Cube (UDM)
• Key Performance Indicator (KPI)
• Case Studies & Summary of the First Session

Watch session 1 here...

Session 2

• Session 2 Intro: Delivering BI Through Microsoft Office System 2007
• Excel 2007 in BI Context
• Data Mining Add-Ins for Excel
• Excel and Multidimensional Data
• Demo: Multidimensional Features of Excel
• Demo: Data Mining with Market Basket Analysis in Excel
• Demo: Browsing Association Rules Data Mining Model in Excel
• Demo: Finding Exceptions Using Data Mining and Excel
• PerformancePoint Services in SharePoint Server
• History and Evolution of PerformancePoint Services
• Monitoring with PPS
• Analytics with PPS
• Reporting and Consolidation with PPS
• PPS Architecture
• Creating KPIs: Indicators
• Normalised KPIs
• Actual Value KPIs
• Scored KPIs
• Demo: Building a KPI, Scorecard and a Dashboard in PPS
• Microsoft Visio and BI
• Summary of the Second Session

Watch session 2 here...

Session 3

• Session 3 Intro: Aggregating Knowledge in a Data Warehouse and Multidimensional Analysis
• Data Warehousing Concepts
• Star Schema
• Snowflake Dimensions
• Hierarchies
• Facts
• Date/Time Dimension
• Slowly Changing Dimensions
• Data Integration and ETL with SSIS
• SSIS Package
• Control and Data Flows in SSIS
• Transformations
• Demo: SSIS for Simple Data Transformations
• Multidimensional Data in SQL Server 2008
• Cubes
• Dimensions in OLAP
• Hierarchies in OLAP
• Measure Groups and Dimension Relationships
• Calculations
• Demo: Reviewing Dimension and Cube Design using BIDS
• Summary of the Third Session

Watch session 3 here...

Session 4

• Session 4 Intro: Finding Hidden Intelligence with Predictive Analytics of Data Mining
• What Does Data Mining Do?
• Server Architecture for Data Mining
• Mining Process
• Classification and Segmentation Scenario with Decision Trees
• Demo: Classification with Decision Trees
• Profitability and Risk Analysis
• Demo: Profitability and Risk Using Neural Networks and Logistic Regression
• Demo: Sequence Clustering
• Demo: Forecasting using Time Series
• Summary of the Fourth Session
• Review and Summary of the Seminar’s Key Learning Points

Watch session 4 here...