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Introduction to Microsoft SQL Server Analysis Services 2008

Introduction to Microsoft SQL Server Analysis Services 2008. Vidas Matelis, Toronto SQL Server User Group November 13, 2008. Quick info about me. Microsoft BI Consultant – SQL Server, SSIS, SSAS, SSRS; over 13 years experience with SQL Server Microsoft SQL MVP

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Introduction to Microsoft SQL Server Analysis Services 2008

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  1. Introduction to Microsoft SQL Server Analysis Services 2008 Vidas Matelis, Toronto SQL Server User Group November 13, 2008

  2. Quick info about me • Microsoft BI Consultant – SQL Server, SSIS, SSAS, SSRS; over 13 years experience with SQL Server • Microsoft SQL MVP • My website: http://www.ssas-info.com • My blog: http://www.ssas-info.com/VidasMatelisBlog/ • 18 Microsoft certification exams – MCP, MCSE-NT4, MCSE-W2K, MCDBA (SQL 2000), MCTS-SQL2005, MCTS-BI2005, MCTS-BI2008, MCIP-BI Developer

  3. Agenda • Quick info about SSAS – what it is and why to use it • SSAS terminology explained – Database, cube, measures, dimensions, attributes • We will create POC SSAS DB on existing SQL Server DB

  4. Short SSAS history and future • Panorama • SQL Server 7.0 • SQL Server 2000 • SQL Server 2005 • SQL Server 2008 • SQL Server 2010 - Kilimanjaro and Gemini

  5. About SSAS • AS is a server-based platform for OLAP and data mining. • Tools - BIDS, SSMS • Query language – Multidimensional Expressions or MDX; for Data Mining - Data Mining Extensions or DMX • MDX Query: SELECT [Date].[Calendar].[Calendar Year].Members ON COLUMNS , [Product].[Category].Members ON ROWS FROM [Adventure Works] WHERE ([Measures].[Reseller Sales Amount] , [Geography].[Geography].[Country].&[Canada] );

  6. Why use SSAS • Speed – MOLAP queries are much faster than relational DB queries (especially summarized data)

  7. Why use SSAS • Speed – MOLAP queries are much faster than relational DB queries (especially aggregated data) • There are many front end tools available that allow users to build reports themselves

  8. Demo 1 – Terminology • Database • Cube • Measure • Dimension • Hierarchy • Attributes

  9. How to use SSAS properly • Extract data from source system(s) • ETL data into relational data warehouse, conforming data from different sources, using surrogate keys • Create SSAS database. • Choose front end and start building reports.

  10. Building POC using SSAS • Choose SQL Server database with data YOU KNOW • Build a fake DW database using views and some tables • Create SSAS database • Choose front end and start building reports.

  11. Demo We will build POC on Adventure Works LT 2008 DB • We will create new SQL Server DB • We will create views that define dimensions and fact table • We will create SSAS Database • We will query data from SSAS Database using Excel

  12. Summary • We learned what SSAS can do for you • We learned how to build POC using SSAS

  13. What to do next • Get more info from http://www.ssas-info.com – articles, papers, webcasts, FAQs • Build POC using your company data and show it to your boss

  14. Q & A • Any questions?

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