1. SQL Server Analysis Services
Introduction to Tabular Mode and BISM

2. Josh Fennessy BI Architect
BlueGranite, Inc (

3. Analysis Services – before today The BI Semantic Model
Agenda
Analysis Services – before today
The BI Semantic Model
Tabular Mode Architecture
Demonstration
Review / questions / comments

4. SQL Server Analysis Services
A brief history
SQL Server Analysis Services

5. SSAS’ story
Based on OLAP technology purchased by MSFT from Panorama Software in ’96
Officially released in ’98 as ‘OLAP Services’ in SQL 7.0
Renamed in SQL 2000 to SSAS
Many new features delivered in SSAS 2005
Data mining
UDM

6. Analysis Services Today
Broad adoption
“Customers in the Magic Quadrant survey report that their Microsoft average deployment sizes are now larger than any other vendor in the survey in terms of users.”
“Use of OLAP functionality by Microsoft customers is more than double that for the rest of the survey respondents.”
Source: Gartner Magic Quadrant for BI Platforms, 2011
Large ecosystem
"Wide availability of skills is among the top reasons customers select Microsoft over competing vendors.”
Source: Gartner Magic Quadrant for BI Platforms, 2011
Highest rated infrastructure and development tools
“Microsoft customers rate its BI platform infrastructure and development tools among the highest compared to other vendors, and a higher percentage of customers use them extensively.”
Source: Gartner Magic Quadrant for BI Platforms, 2011

7. Analysis Services Tomorrow
Build on the strengths and success of Analysis Services and expand its reach to a much broader user base
Embrace the relational data model – well understood by developers and IT Pros
BI Semantic
Model
Analysis Services Vision
Bring together the relational and multidimensional models under a single unified BI platform – best of both worlds!
Provide flexibility in the platform to suit the diverse needs of BI applications

8. Business Intelligence Semantic Model

9. BI Semantic Model One Model for all End User Experiences Team BI
Client Tools Analytics, Reports, Scorecards,
Dashboards, Custom Apps
Data Sources
Databases, LOB Applications, OData Feeds,
Spreadsheets, Text Files
BI Semantic Model
Data model
Business logic
and queries
Data access
Team BI
PowerPivot for SharePoint
Personal BI
PowerPivot for Excel
Organizational BI
Analysis Services

10. BI Semantic Model What about existing Analysis Services applications?
Existing applications
Based on Unified Dimensional Model
Existing applications
Based on Unified Dimensional Model
Existing applications
Every UDM becomes a BI Semantic Model
New applications
New technology options
After RTM
“Denali”

11. BISM Architecture BI Semantic Model Data model Business logic
Third-party
applications
Reporting
Services
SharePoint
Insights
Excel
PowerPivot
BI Semantic Model
Multi-
dimensional
Data model
Tabular
Business logic
and queries
MDX
DAX
Direct
Query
Data access
ROLAP
MOLAP
VertiPaq
Databases
LOB Applications
Files
OData Feeds
Cloud Services

12. BISM Features Flexibility Richness Scalability
Multi-dimensional and tabular modeling experiences
MDX and DAX for business logic and queries
Cached and passthrough storage modes
Choice of end-user BI tools
Rich data modeling capabilities
Sophisticated business logic using MDX and DAX
Fine-grained security – row/cell level
Enterprise capabilities – multi-language and perspectives
VertiPaq for high performance, MOLAP for mission critical scale
DirectQuery and ROLAP for real-time access to data sources
State-of-the-art compression algorithms
Scales to largest enterprise servers

13. Scenario: Excel over Sales Model
End
User
Model Developer
BI Semantic Model
Multi-
dimensional
Data model
Tabular
Business logic
and queries
MDX
DAX
Data access
VertiPaq
SQL Server
Dynamics CRM

14. What does BISM do for me?
Quiz time! Pick which one is a Tabular Model.

15. SSAS Data Access & Storage
xVelocity
In-memory column store… typical 10x compression
Brute force memory scans… high performance by default… no tuning required
Basic paging support… data volume mostly limited to physical memory
MOLAP
Disk based store… typical 3x compression
Disk scans with in-memory subcube caching… aggregation tuning required
Extensive paging support… data volumes can scale to multiple terabytes
DirectQuery
Passes through DAX queries & calculations… fully exploits backend database capabilities
No support for MDX queries… no support for data sources other than SQL Server (in Denali)
ROLAP
Passes through fact table requests… not recommended for large dimension tables
Supports most relational data sources… no support for aggregations except SQL Server indexed views

16. Custom Calculations DAX MDX
Based on Excel formulas and relational concepts – easy to get started
Complex solutions require steeper learning curve – row/filter context, Calculate, etc.
Calculated columns enable new scenarios, however no named sets or calc members
MDX
Based on understanding of multidimensional concepts – higher initial learning curve
Complex solutions require steeper learning curve – CurrentMember, overwrite semantics, etc.
Ideally suited for apps that need the power of multidimensional calculations – scopes, assignments, calc members

17. How should I build my SSAS solution?
Two Visual Studio (BIDS) project types in Denali
Multidimensional project – with MDX and MOLAP/ROLAP
Tabular project – with DAX and VertiPaq/DirectQuery
Some Considerations
Favors Tabular/DAX
Favors Multi-dim/MDX
Cube write-back needed?
Parent/Child needed?
4/4/5 Fiscal Calendars
Excessive Many to Many
Extreme data volumes
Large MD investment?
Large RAM footprint a negative?
Financial models (budgeting/forecasting)
Real-time (Direct Query)
Counting what’s not present
Excel-based Modeling Attractive?
Non-relational data sources?
In-memory performance benefit
Lower learning curve desirable?
Simpler models (Sales, OLTP transaction analysis, etc.)

18. Other thoughts… Multidimensional isn’t dead
DAX doesn’t address some common modeling requirements
Vertipaq has more limited storage (models must fit in RAM)
Many simple data modeling tasks are easier in DAX; many complex ones are easier in MDX
As DAX/BISM evolves it will close the gap, but not for a couple years
At RTM Power View is a Tabular-only technology
This will probably force a decision to tabular in some scenarios
Business Analytics is complex no matter what expression language is used
DAX isn’t a silver bullet, but it probably is easier to learn to implement basic/intermediate calculations than MDX for those new to OLAP
Should I port my Multidimensional cube to Tabular during migration?
If calculations aren’t complex and all necessary features are available in Tabular Mode/DAX, you should consider doing so to achieve better performance and Power view support
If the existing calculations and installed

19. Other Thoughts… Process for Multidimensional to Tabular migration
Evaluate features in the gap
Many-to-many (can be done in calculations however)
Parent/Child
Cube writeback
Calculated members
Etc.
How difficult to rewrite calculations in DAX?
Is the data too large for Tabular mode? (terabytes+)
Will the server have enough RAM?
Existing application impact?
Does Tabular/DAX solve unmet needs?
Multi-select issues in calculations
Counting what’s not there needs
Performance issues (ad-hoc w/o aggregation issues)

20. Demo

21. REview BISM is designed to make USER experience smoother
Complexity still exists in data modeling
Multi-dimensional is not gone
DAX is still complex

22. Thank you!
Questions? me -