SQL Server & Business Intelligence
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Data Warehouse Workshop

2013-02-07, Microsoft (Kista)

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Data Warehouse Workshop

This is your opportunity to learn data warehousing from the top international Business Intelligence experts and presenters Thomas Kejser and Davide Mauri. During this workshop they will be teaching their learnings and best practices from working with numerous Business Intelligence projects, including the toughest and most challenging Microsoft Business Intelligence projects in the world.


In-memory technology is ruling and people keep telling you that a BI solution can be created by just connecting directly to the source of data, and that's it. Wrong! A Data Warehouse is still needed and vital for the success of a Business Intelligence solution, no matter which technology you'll use to read, process and present all the gathered data. A Data Warehouse holds the data upon which analysts, decision makers and managers will take their decisions: it must deliver good, high-quality, on-time, certified data. That’s the only way to turn data into information and information into money. In this workshop the Data Warehouse topic will be defined and exposed in detail, starting from the basic theory, and going through well-known models and design patterns, approaches and tools that are needed to build and maintain a Data Warehouse, capable of being flexible in order to support the fast changes needed by today's business, but also with a well-known and well-defined structure in order to support the "engineerization" of its development process, making it cost effective.


Thomas Kejser is a former Principal Program Manager of the Microsoft SQL Server CAT team, supporting the toughest Microsoft SQL Server data warehouse projects in the world. He was also one of the teachers of the SSAS Maestros programme. Davide Mauri is a frequent international speaker and co-author of "Smart Business Intelligence Solution With SQL Server 2008" published by Microsoft Press. He's developed BI solutions for very large international companies. Davide is also the author of the DTLoggedExec tool.


Introduction to the slide approach

  • From the beginning to the end and back
“Agile” Approach
  • Agile concepts applied to Data Warehousing
The need for a Data Warehouse
  • The added value of a Data Warehouse
  • Self-Service BI & Other Stories
Modelling the Data Warehouse
  • Kimball vs Inmon (and other known modelling techniques)
  • Dimensions, Facts & Measures
  • Star Schema & Snowflake Schema
  • Types of Fact Tables
  • Transactional
  • Snapshot
  • Temporal
  • Enterprise Data Warehouse
  • ETL Manually generated vs automatically Generated
Dimension Design
  • SCD1, SCD2, SCD3
  • Dealing with Huge Dimension
  • Junk Dimension & Other Things
Facts Design
  • Transactional
  • Snapshot
  • Temporal
  • Many-to-many Relationship
Populating the Data Warehouse
  • Staging Source Data
  • Maps & Key Tables
  • Defining the ETL architecture
  • Rules for the ETL solution
  • SSIS Package Naming Conventions
  • Implementation of the ETL Solution
  • Loading the Dimensions
  • Loading the Fact Tables
    • Incremental vs Full
    • Partitioning & Parallelism
Handling Changes
  • Archiving Sources
  • Moving from one SCD to another
  • Detecting Dependencies
  • Unit Testing and Data Stability
Automating the Development
After the Data Warehouse

Side Panels

Topics that will be explained and touched during the entire workshop and not in a specific moment or order

Data Warehouse Architecture

  • Rules for creating the database
  • Naming conventions
  • Object Usage and Scope
  • Rules for Dimensions
Tools that helps
  • Available free tools to help building the Data Warehouse

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