SQL Server Analysis Services

Report
SQL Server Analysis Services
Introduction to Tabular Mode and BISM
Josh Fennessy
• BI Architect
– BlueGranite, Inc (http://www.blue-granite.com)
Agenda
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Analysis Services – before today
The BI Semantic Model
Tabular Mode Architecture
Demonstration
Review / questions / comments
A brief history
SQL SERVER ANALYSIS
SERVICES
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
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
ANALYSIS SERVICES TOMORROW
Build on the strengths
and success of Analysis
Services and expand its
reach to a much broader
user base
Bring together the
relational and
multidimensional
models under a single
unified BI platform –
best of both worlds!
Embrace the relational
data model – well
understood by developers
and IT Pros
Provide flexibility in the
platform to suit the diverse
needs of BI applications
Business Intelligence
Semantic Model
BI SEMANTIC MODEL
One Model for all End User Experiences
Client Tools
Analytics, Reports, Scorecards,
Dashboards, Custom Apps
BI Semantic Model
Data model
Business logic
and queries
Data access
Data Sources
Databases, LOB Applications, OData Feeds,
Spreadsheets, Text Files
Personal BI
PowerPivot for Excel
Team BI
Organizational BI
PowerPivot for SharePoint
Analysis Services
BI Semantic Model
What about existing Analysis Services applications?
Existing applications
Existing applications New applications
Based on Unified Dimensional
Model
Every UDM becomes a BI
Semantic Model
New technology options
After RTM
“Denali”
BISM ARCHITECTURE
Third-party
applications
Reporting
Services
Excel
SharePoint
Insights
PowerPivot
BI Semantic Model
Data model
Multidimensional
Tabular
MDX
DAX
Business logic
and queries
Data access
Databases
LOB Applications
ROLAP
Files
MOLAP
OData Feeds
VertiPaq
Direct
Query
Cloud Services
BISM FEATURES
Flexibility
Richness
• Multi-dimensional and tabular
modeling experiences
• Rich data modeling
capabilities
• MDX and DAX for business
logic and queries
• Sophisticated business
logic using MDX and DAX
• Cached and passthrough
storage modes
• Fine-grained security –
row/cell level
• Choice of end-user BI tools
• Enterprise capabilities –
multi-language and
perspectives
Scalability
• 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
SCENARIO: EXCEL OVER SALES
MODEL
End
User
SQL Server
Dynamics CRM
Model Developer
WHAT DOES BISM DO FOR ME?
Quiz time! Pick which one is a Tabular Model.
SSAS DATA ACCESS & STORAGE
 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
 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)
 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
 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
CUSTOM CALCULATIONS
DAX
 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
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
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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)
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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.)
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
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)
Demo
REVIEW
• BISM is designed to make USER experience smoother
• Complexity still exists in data modeling
• Multi-dimensional is not gone
• DAX is still complex
THANK YOU!
Questions? Email me - [email protected]

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