Microsoft SQL Server Analysis Services (SSAS) - A Practical Introduction

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Patrick Sheehan of Microsoft covers platform architecture, data warehousing methodology, and multi-dimensional cube development.

You will learn:

* How to develop and deploy data cubes using SQL Server Analysis Services (SSAS)
* Optimal data warehouse methodology for use with SSAS
* Tips/tricks for designing & building cubes over no warehouse/suboptimal source system (it happens)
* Cube processing types - How/why to use each
* Cube design practices + How to build and deploy cubes!

Published in: Data & Analytics, Technology
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Microsoft SQL Server Analysis Services (SSAS) - A Practical Introduction

  1. 1. Silicon Valley SQL Server User Group Tonight’s Agenda May 20, 2014  6:30 – 7:00 pm Food and Networking  7:00 – 7:10 pm Introductions  7:10 – 8:10 pm Patrick Sheehan, Microsoft  8:10 – 8:30 pm Discussion (Q&A)
  2. 2. Parent Organizations  Bay Area Association of Database Developers  BAADD www.baadd.org  Professional Association of SQL Server  PASS www.sqlpass.org
  3. 3. Sponsors
  4. 4. Upcoming Meetings  San Francisco – Thurs, June 5  Dimensional Modeling, The Basics & Beyond  Dan Bulos, Symmetry  San Francisco – Wed, June 11  SQL Server Implementation Frameworks From Dev to Prod  Prakash Heda, Advent Software
  5. 5. Announcements  Attendee Announcements  New Jobs  New Projects  Projects completed  Upcoming learning opportunities
  6. 6. Patrick Sheehan  Data Platform Architect at Microsoft’s Silicon Valley Technology Center (SVC MTC)  Previously with Microsoft Consulting Services (MCS) as an engineer, architect, and enterprise strategist  Specialties:  SQL Server  Business Intelligence  Big Data  Enterprise & Solutions Architecture  Cloud Computing
  7. 7. SQL Server Analysis Services SSAS – 2012 Fundamentals
  8. 8. What is Analysis Services? • Online Analytical Processing (OLAP) engine • Designed for data analysis, mining, and reporting • Contains Databases • Contains Cubes • Cubes are multi-dimensional data sets • Sourced from Facts • Tables which contain measures • …and Dimensions • Tables which contain attributes Reference: http://technet.microsoft.com/en-us/library/bb522625.aspx
  9. 9. Use Cases • Data abstraction layer • Ad hoc reporting • Data mining • Data warehousing • Kimball Methodology recommended
  10. 10. DEMO
  11. 11. Prerequisites • Install SQL Server 2012 + SP1 • Developer Edition, Eval, or Enterprise • Eval (180 day) can be obtained (free) here: http://www.microsoft.com/en- us/download/details.aspx?id=29066 • SQL Server Engine • SQL Server Analysis Services • Workstation Components • SQL Server Data Tools (SSDT) Download SSDT here: http://msdn.microsoft.com/en-us/library/hh272686(v=vs.103).aspx
  12. 12. Tutorials Analysis Services Tutorials (SSAS) http://technet.microsoft.com/en-us/library/hh231701.aspx Multidimensional Modeling (Adventure Works Tutorial) http://technet.microsoft.com/en-us/library/db55e226-601a-4026-8651-573195555a59
  13. 13. Download samples http://msftdbprodsamples.codeplex.com/
  14. 14. Set up environment • Move .mdf to SQL Server Data directory (e.g. C:Program FilesMicrosoft SQL ServerMSSQL11.SQL2012MSSQLDATA) • Attach .mdf to instance • NOTE: if error is received, it is due to missing log file. Click on the .ldf file listed in the Attach Database dialogue box, then click Remove (a new log file will automatically be created in the default path) • Extract .sln from .zip • Open solution and reset connection strings to local db instance
  15. 15. Solution structure • Data Sources node • Connection strings to source • Data Source Views node • XML abstraction layer • Cubes node • Define dim/fact relationships, aggregations (calculations), partitions, mode • Dimensions node • Contains dimensions • Roles node • Define access to cube
  16. 16. Cube fundamentals • Measure groups • Contain measures • Set properties (e.g. formatting) • Dimensions • Contain attributes • Set properties (e.g. visibility) • Define relationships (to key & each other) • Define hierarchies • Deployment • Processing • Affects of FULL versus
  17. 17. Multi-dimensonal Expression Language (MDX) Example Syntax [ WITH <SELECT WITH clause> [ , <SELECT WITH clause> ... ] ] SELECT [ * | ( <SELECT query axis clause> [ , <SELECT query axis clause> ... ] ) ] FROM <SELECT subcube clause> [ <SELECT slicer axis clause> ] [ <SELECT cell property list clause> ] SELECT NON EMPTY { [Measures].[Reseller Order Quantity], [Measures].[Reseller Gross Profit], [Measures].[Reseller Sales Amount] } ON COLUMNS, NON EMPTY { ([Product].[Product Categories].[Product].ALLMEMBERS * [Date].[Fiscal].[Date].ALLMEMBERS ) } DIMENSION PROPERTIES MEMBER_CAPTION, MEMBER_UNIQUE_NAME ON ROWS FROM [Adventure Works] CELL PROPERTIES VALUE, BACK_COLOR, FORE_COLOR, FORMATTED_VALUE, FORMAT_STRING, FONT_NAME, FONT_SIZE, FONT_FLAGS Reference: http://technet.microsoft.com/en-us/library/ms145595.aspx
  18. 18. MDX “Heads up” • MDX my look like T-SQL, but do not be fooled! It isn’t! • MDX is a different way to think about data • MDX is designed to provide tabular output from multidimensional sources Reference: http://msdn.microsoft.com/en-us/library/ms145506.aspx Books: MDX Solutions: With Microsoft SQL Server Analysis Services 2005 and Hyperion Essbase – George Spofford (&others) The Data Warehouse Toolkit: The Definitive Guide to Dimensional Modeling – Ralph Kimball
  19. 19. Working with Cubes • Microsoft Excel is #1 app (>1billion worldwide deployments) • Native integration with SSAS • SQL Server Reporting Services (SSRS) • Native integration with SSAS • Multidimensional Programming (see: http://technet.microsoft.com/en-us/library/bb500153.aspx) • ADOMD.NET • .NET provider for communication with SSAS (via XMLA) • Analysis Services Scripting Language (ASSL) • Extends XMLA • Analysis Management Objects (AMO) • SSAS management classes

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