The document discusses best practices for designing and implementing SQL Server Analysis Services (SSAS), focusing on incremental processing, cube and dimension designs, and the Microsoft Business Intelligence framework. It includes insights from Dan English, a principal consultant at Magenic, and outlines the importance of efficient data handling, user-defined hierarchies, and optimal storage strategies. Additionally, it briefly compares PowerPivot and provides resources for further information.

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

15. Cube Design Demos
Demos

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

18. SSAS Incremental Processing

19. SSAS Incremental Processing

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

24. Questions

25. Thank you
http://denglishbi.spaces.live.com
http://twitter.com/denglishbi
info@magenic.com
www.magenic.com