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SSAS Design Best Practices and
Incremental Processing

Dan English
Principal Consultant – Business Intelligence Architect
DanE@magenic.com
http://denglishbi.spaces.live.com
http://twitter.com/denglishbi
Who am I?
             Dan English
             http://denglishbi.spaces.live.com/



    Developing with Microsoft technologies for over 12 years
    Over 5 years experience with Data Warehousing and Business
     Intelligence
    Architect and develop dashboard solutions for enterprise
     reporting and monitoring
    Experienced in ETL and Analysis Services development,
     requirements gathering, and data modeling
    Microsoft Certified IT Professional (MCITP) and Microsoft
     Certified Technology Specialist (MCTS)
    PASSMN 2009/2010 – Executive Board Chair (President)
    Twitter – http://twitter.com/denglishbi
    YouTube Videos - http://youtube.com/user/denglishbi
Who is Magenic?
 Founded in 1995, Magenic is a technical
    consulting firm focused exclusively on
    Microsoft technologies and has designed
    and delivered more than 500 Microsoft-
    based applications
   Headquartered in Minneapolis, with offices
    in Chicago, Boston, Atlanta and San
    Francisco
   2005 Microsoft Partner of the Year, Custom
    Development Solutions – Technical
    Innovation
   2007 Microsoft Partner of the Year Finalist,
    Data Management
   Microsoft Gold Certified Partner and
    National Systems Integrator
   Over 200 consultants
Quick Audience Poll
 How many are currently using Analysis Services?

 How many are considering Analysis Services?

 What are you using Analysis Services for and how?

 Anyone currently looking at PowerPivot?
Today’s Agenda
 •   Microsoft Business Intelligence Overview
 •   Overview of Analysis Services
 •   AMO Warnings
 •   Dimension Designs / Demos
 •   Cube Designs / Demos
 •   Incremental Processing
 •   PowerPivot Comparison - quick mention
 •   Questions
Microsoft Business Intelligence Overview
        Business User Experience
                                         •Self-Service access & insight
                                         •Data exploration & analysis
                                         •Predictive analysis
                                         •Data visualization
                                         •Contextual visualization
     Business Collaboration Platform     •Dashboards & Scorecards
                                         •Excel Services
                                         •Web based forms & workflow
                                         •Collaboration
                                         •Search
                                         •Content Management
                                         •LOB data integration

     Data Infrastructure & BI Platform   •Analysis Services
                                         •Reporting Services
                                         •Integration Services
                                         •Master Data Services
                                         •Data Mining
                                         •Data Warehousing
BI Maturity Model




                    By Wayne Eckerson, Director of Research, TDWI
SSAS Overview




 Source       Data mart      OLAP
 Data                        Engine




   •   OLAP Database                  In North America in 2003 there were
                                      $21,935,649 in Bike Sales and 9,975
   •   Slice-and-dice
                                      Bikes Sold
   •   Drilldown / cross-drill
   •   Aggregated values
AMO Warnings - Best Practice Alerts

                            SQL Server Best
                               Practice
                             Analyzer alerts
                              embedded –
                              database or
                              object level
Dimension Designs
• Define only required attributes – add more later as needed
• Create user-defined hierarchies – navigation paths
• Create attribute relationships – optimize storage and define integrity
• Define proper key columns for attributes – preferably numeric
• Use BIDS Helper – Dimension Health Check
• Set Attribute Relationship Type appropriately – flexible or rigid
• Avoid High Cardinality attributes as hierarchies – most likely member
  properties
• Set Order By appropriately – name, key, related attribute
• Set dimension and attribute Types appropriately – Account, Time, etc.
• Set attribute Instance Selection appropriately – needed for Report
  Models
Dimension Designs


                    In SSAS 2008 there is a
                    new attribute relationships
                    tab in the dimension
                    designer which provides an
                    easy to understand
                    interface and diagram.
Best Practice Alerts / Dimension Designs



              Demos
Cube / Calculation Designs
 • Reuse dimensions multiple times instead of duplicating (role playing) –
   lower storage costs and maintenance
 • Use proper numeric data types – reduce storage costs
 • Split measure groups into separate cubes if unrelated – avoid confusion
   and improve query performance
 • Place distinct count measures in separate measure groups – different
   aggregations
 • Set IgnoreUnrelatedDimensions on measure group appropriately
 • Remove simple calculations like addition or subtraction (if possible) –
   move to ETL, DSV, or a Measure
 • Add a default NULL measure to cube – improve performance, reduce
   unnecessary querying
 • Group measures / calculations with proper measure groups and folders
 • Provide proper formatting on all measures and calculations – currency,
   standard, decimals, percentage, etc.
Cube Partitions / Aggregation Designs
 • Create partitions in measure groups with more than 20MM rows
 • Combine partitions that are too small to improve performance – don’t
   create unnecessary partitions
 • Don’t create too many aggregations – can have negative impact on
   queries
 • Enable Query Logging for UBO
 • Manual aggregations 20 to 30% gain, UBO 70 to 80% gain (actual
   usage)
 • Set member and row counts for aggregation design algorithm
 • Evaluate whether rigid or flexible attribute relationships are being used
   in aggregation designs – flexible ones will be dropped if there are
   changes
Cube Design Demos



            Demos
Demo Screenshots – Cube Designs




               CREATE MEMBER
               CURRENTCUBE.MEASURES.UseAsDefaultMeasure
               AS NULL,
               VISIBLE = 0;
SSAS Incremental Processing

 Reasons for implementing:

 • Data volumes are extremely large
 • Reduce
    • End-user down time
    • Processing time
    • Impact on source
    • Impact on processing server
 • More frequent loads – every X hours instead of nightly
SSAS Incremental Processing
SSAS Incremental Processing
PowerPivot – Excel 2010 Add-in
Self-service analysis
Work with massive
                    delivered thru Excel
 amounts of data
                            2010
PowerPivot – a few tidbits

 What you do get…
 • OLAP engine (in-memory cube – Vertipaq)
 • DAX functions – Excel like with intellisense
 • Excel user interface
 • PivotTables and Charts

 What you don’t get…
 • Dynamic user level security
 • Hierarchy support and parentchild
 • Attribute properties and cube actions
 • Robust Enterprise OLAP Solution
Resources
Microsoft BI Site
http://www.microsoft.com/bi

Microsoft BI Resource Center
http://technet.microsoft.com/bi

William E. Pearson, III DB Journal Tutorials
http://www.databasejournal.com/article.php/1459531

SSAS Multi-Dimensional SQL Developer Center
http://technet.microsoft.com/en-us/sqlserver/cc510300.aspx

Channel9 MSDN BI Screencasts
http://channel9.msdn.com/Showforum.aspx?forumid=38&tagid=277

SQL Server Best Practices
http://msdn.microsoft.com/en-us/sqlserver/bb671432.aspx

Microsoft Virtual Labs (TechNet and MSDN)
http://www.microsoft.com/events/vlabs/default.mspx

Microsoft BI Virtual Labs
http://denglishbi.spaces.live.com/blog/cns!CD3E77E793DF6178!349.entry

Magenic Blogs
http://blog.magenic.com/blogs
Questions
Thank you


        http://denglishbi.spaces.live.com
            http://twitter.com/denglishbi


                info@magenic.com
                www.magenic.com

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SSAS Design & Incremental Processing - PASSMN May 2010

  • 1. SSAS Design Best Practices and Incremental Processing Dan English Principal Consultant – Business Intelligence Architect DanE@magenic.com http://denglishbi.spaces.live.com http://twitter.com/denglishbi
  • 2. Who am I? Dan English http://denglishbi.spaces.live.com/  Developing with Microsoft technologies for over 12 years  Over 5 years experience with Data Warehousing and Business Intelligence  Architect and develop dashboard solutions for enterprise reporting and monitoring  Experienced in ETL and Analysis Services development, requirements gathering, and data modeling  Microsoft Certified IT Professional (MCITP) and Microsoft Certified Technology Specialist (MCTS)  PASSMN 2009/2010 – Executive Board Chair (President)  Twitter – http://twitter.com/denglishbi  YouTube Videos - http://youtube.com/user/denglishbi
  • 3. Who is Magenic?  Founded in 1995, Magenic is a technical consulting firm focused exclusively on Microsoft technologies and has designed and delivered more than 500 Microsoft- based applications  Headquartered in Minneapolis, with offices in Chicago, Boston, Atlanta and San Francisco  2005 Microsoft Partner of the Year, Custom Development Solutions – Technical Innovation  2007 Microsoft Partner of the Year Finalist, Data Management  Microsoft Gold Certified Partner and National Systems Integrator  Over 200 consultants
  • 4. Quick Audience Poll  How many are currently using Analysis Services?  How many are considering Analysis Services?  What are you using Analysis Services for and how?  Anyone currently looking at PowerPivot?
  • 5. Today’s Agenda • Microsoft Business Intelligence Overview • Overview of Analysis Services • AMO Warnings • Dimension Designs / Demos • Cube Designs / Demos • Incremental Processing • PowerPivot Comparison - quick mention • Questions
  • 6. Microsoft Business Intelligence Overview Business User Experience •Self-Service access & insight •Data exploration & analysis •Predictive analysis •Data visualization •Contextual visualization Business Collaboration Platform •Dashboards & Scorecards •Excel Services •Web based forms & workflow •Collaboration •Search •Content Management •LOB data integration Data Infrastructure & BI Platform •Analysis Services •Reporting Services •Integration Services •Master Data Services •Data Mining •Data Warehousing
  • 7. BI Maturity Model By Wayne Eckerson, Director of Research, TDWI
  • 8. SSAS Overview Source Data mart OLAP Data Engine • OLAP Database In North America in 2003 there were $21,935,649 in Bike Sales and 9,975 • Slice-and-dice Bikes Sold • Drilldown / cross-drill • Aggregated values
  • 9. AMO Warnings - Best Practice Alerts SQL Server Best Practice Analyzer alerts embedded – database or object level
  • 10. Dimension Designs • Define only required attributes – add more later as needed • Create user-defined hierarchies – navigation paths • Create attribute relationships – optimize storage and define integrity • Define proper key columns for attributes – preferably numeric • Use BIDS Helper – Dimension Health Check • Set Attribute Relationship Type appropriately – flexible or rigid • Avoid High Cardinality attributes as hierarchies – most likely member properties • Set Order By appropriately – name, key, related attribute • Set dimension and attribute Types appropriately – Account, Time, etc. • Set attribute Instance Selection appropriately – needed for Report Models
  • 11. Dimension Designs In SSAS 2008 there is a new attribute relationships tab in the dimension designer which provides an easy to understand interface and diagram.
  • 12. Best Practice Alerts / Dimension Designs Demos
  • 13. Cube / Calculation Designs • Reuse dimensions multiple times instead of duplicating (role playing) – lower storage costs and maintenance • Use proper numeric data types – reduce storage costs • Split measure groups into separate cubes if unrelated – avoid confusion and improve query performance • Place distinct count measures in separate measure groups – different aggregations • Set IgnoreUnrelatedDimensions on measure group appropriately • Remove simple calculations like addition or subtraction (if possible) – move to ETL, DSV, or a Measure • Add a default NULL measure to cube – improve performance, reduce unnecessary querying • Group measures / calculations with proper measure groups and folders • Provide proper formatting on all measures and calculations – currency, standard, decimals, percentage, etc.
  • 14. Cube Partitions / Aggregation Designs • Create partitions in measure groups with more than 20MM rows • Combine partitions that are too small to improve performance – don’t create unnecessary partitions • Don’t create too many aggregations – can have negative impact on queries • Enable Query Logging for UBO • Manual aggregations 20 to 30% gain, UBO 70 to 80% gain (actual usage) • Set member and row counts for aggregation design algorithm • Evaluate whether rigid or flexible attribute relationships are being used in aggregation designs – flexible ones will be dropped if there are changes
  • 16. Demo Screenshots – Cube Designs CREATE MEMBER CURRENTCUBE.MEASURES.UseAsDefaultMeasure AS NULL, VISIBLE = 0;
  • 17. SSAS Incremental Processing Reasons for implementing: • Data volumes are extremely large • Reduce • End-user down time • Processing time • Impact on source • Impact on processing server • More frequent loads – every X hours instead of nightly
  • 20. PowerPivot – Excel 2010 Add-in
  • 21. Self-service analysis Work with massive delivered thru Excel amounts of data 2010
  • 22. PowerPivot – a few tidbits What you do get… • OLAP engine (in-memory cube – Vertipaq) • DAX functions – Excel like with intellisense • Excel user interface • PivotTables and Charts What you don’t get… • Dynamic user level security • Hierarchy support and parentchild • Attribute properties and cube actions • Robust Enterprise OLAP Solution
  • 23. Resources Microsoft BI Site http://www.microsoft.com/bi Microsoft BI Resource Center http://technet.microsoft.com/bi William E. Pearson, III DB Journal Tutorials http://www.databasejournal.com/article.php/1459531 SSAS Multi-Dimensional SQL Developer Center http://technet.microsoft.com/en-us/sqlserver/cc510300.aspx Channel9 MSDN BI Screencasts http://channel9.msdn.com/Showforum.aspx?forumid=38&tagid=277 SQL Server Best Practices http://msdn.microsoft.com/en-us/sqlserver/bb671432.aspx Microsoft Virtual Labs (TechNet and MSDN) http://www.microsoft.com/events/vlabs/default.mspx Microsoft BI Virtual Labs http://denglishbi.spaces.live.com/blog/cns!CD3E77E793DF6178!349.entry Magenic Blogs http://blog.magenic.com/blogs
  • 25. Thank you http://denglishbi.spaces.live.com http://twitter.com/denglishbi info@magenic.com www.magenic.com