1. Analysis Services for the Absolute Beginner
Peter Shore
SQL Saturday Cincinnati

2. Agenda Introduction What is Analysis Services? Some History
About the session
About the speaker
What is Analysis Services?
Some History
How do I use Analysis Services?

3. About The Session Abstract:
Publications across the globe have called “data the new oil.” However, the value of oil is what the oil can be turned into. Similarly, the value in data is in what you derive from it, not the data itself.
Regardless of the title you carry, DBA, developer, report writer, ETL developer, manager etc., now is the time to make an acquaintance of Analysis Services. Come, join in as we define basic terms, investigate a few uses cases and see some simple examples. You will soon see that if data is the new oil, Analysis Services, on-premises or in the cloud, is a key component in the new refinery.

4. Specialize in remote database administration, operating system, and enterprise application support services
24x7, 100% onshore support across all major database platforms including SQL Server, MySQL, PostgreSQL, Oracle, Oracle Applications, and DB2
Full suite of Microsoft Business Intelligence and Database Activity Monitoring services available
Currently support hundreds of customers and thousands of databases daily

5. About Me SQL Server Database Administrator - RDX
Intentionally Accidental DBA
Over 20 years IT experience
Server Engineer
Desktop Engineer
Network Infrastructure
Desk side support
President CBusPASS
Member Multiple Virtual Chapters
How to find me

6. What is Analysis Services?
What Microsoft says*
Analysis Services is an analytical data engine used in decision support and business analytics.
Provides Enterprise Grade Semantic Models
For business reports
For client applications
For Excel, Power BI, Reporting Services, other visualization applications
Analysis Services Available in two platforms
Azure Analysis Services
SQL Server Analysis Services *

7. What is Analysis Services?
Simple
Easily understood
Jargon free
Party time!

8. What is Analysis Services?
What Peter says:
Analysis Services is an abstraction layer
Abstraction layer is a method of hiding implementation details
Abstraction layer allows facilitation of interoperability*
Oracle
MySQL
CosmosDB
Hadoop/Hive
Active Directory
SAP Hana
JSON *

9. What is Analysis Services?
What Peter says:
Analysis Services is a caching layer
Cache = “Hardware or software layer that stores data, so future requests can be served faster”
Accelerates “clicky clicky draggy draggy” reporting (think PowerBI)
Simplified Management Point
Security all in the semantic model
Consistent connectivity point
IT Governance of democratized BI

10. Some History SQL Server 7.0 SQL Server 2000 OLAP Services Introduced
On-Line Analysis Processing
Introduces two new technologies
OLE DB for OLAP
Multidimensional Expression (MDX)
Microsoft begins a journey of democratized BI
SQL Server 2000
Name changed to Analysis Services
Richer Dimensions
Richer Cube Definition
Market Leader

11. Some History SQL Server 2005/Analysis Services 2005
Enterprise class OLAP features
Enterprise class Data mining
Increase increasingly sophisticated problems
Feature Rich
Scalable
Higher performing
Unified Dimensional Model (UDM)
Cubes
Dimensions
Foundation of the BI Stack
PivotTables, PivotCharts, PerformancePoint Services, SSRS

12. Some History SQL Server 2008R2/Analysis Services 2008R2
Non-Traditional data sources
Odata Feeds
Spreadsheets
Text Files
PowerPivot
Data Analysis Expressions (DAX)
SQL Server 2012
Brings together Multidimensional & Tabular models
Self service, team and enterprise BI Solutions

13. Terms Democratized BI OLAP Multidimensional Expression (MDX)
Extending access to business intelligence to a greater number of people
Outside of IT
Not necessarily data specialists
Domain Experts
Stress data governance
OLAP
An approach to swiftly answering multidimensional analytical queries
Multidimensional Expression (MDX)
Query language of OLAP cubes
Calculation language
Syntax similar to spreadsheet formulas

14. Terms Model Cube aka OLAP Cube Dimensions
Logical inter-relationship and data flow between different data elements
Cube aka OLAP Cube
Method of storing data in a multidimensional forum
Data (measures) are categorized by dimensions
Dimensions
Structure that categorizes facts and measures
Provide structured labeling information

15. Terms Facts Measures Odata Feed Single record Represents a transaction
Lowest level of granularity
Composed of dimension keys and measures
Measures
Property on which calculations can be made
Odata Feed
Open Data Protocol
Allow consumption of data from queryable REST APIs

16. BI Semantic Model

17. BI Semantic Model

18. BI Semantic Model Data Model Tabular Model Multidimensional Model
Developed in Excel or SQL Server Data Tools (SSDT)
Tables, Columns, Relationships
Can be developed tabular but consumed multidimensional
Exposes a multidimensional (cube) interface
Multidimensional Model
Developed in SSDT
Made up of dimensions and measures

19. BI Semantic Model Business Logic/Queries DAX MDX
Introduced in PowerPivot with SQL Server 2008R2
Included in SSAS in SQL Server 2012
Designed for tabular models
Based on Excel formulas
Eventually to be used against multidimensional
MDX
Calculation and query language
Multidimensional
Can be used against tabular models

20. BI Semantic Model Data Access MOLAP ROLAP xVelocity Storage Engine
Multidimensional OLAP
Not in the relational database, rather in proprietary formats
ROLAP
Relational OLAP
Large amounts of data
Can be slow, limited by SQL
xVelocity Storage Engine
VertiPaq
In –memory and memory optimized storage engine
Same engine generates column store indexes

21. Analysis Services Database
Collection of
Data sources
Data source views
Cubes
Dimensions
Roles
Optionally includes
Structures for data mining
Custom libraries

22. Multi dimensional Model
High performance queries against business data
Cubes
Relate measures and dimensions
Measure
A fact that is a transactional value or measurement a user may want to aggregate
Sales Amount
Sales Price
Dimension
Group of attributes that represent an area of interest related to the measures
Customer
Location
SQL Server 2000 and later

23. Tabular Model Run in-memory or Direct Query
Accesses data directly from backend resources
Accessed as if Multidimensional
Uses DAX & MDX
SQL Server 2012 and later

24. Tabular vs. Multidimensional
Multidimensional
Tabular
Actions
Yes No
Aggregations
Calculated Column
Calculated Measures
Calculated Tables
Custom Assemblies
Custom Rollups
Default Member
Display folders
Distinct Count
Yes (via DAX)
Drillthrough
Yes (depends on client application)
Hierarchies
KPIs

25. Tabular vs. Multidimensional
Linked objects
Yes
Yes (linked tables)
M expressions No
Many-to-many relationships
No (but there is bi-directional cross filters at 1200 and higher compatibility levels)
Named sets
Ragged Hierarchies
Parent-child Hierarchies
Yes (via DAX)
Partitions
Perspectives
Row-level Security
Object-level Security
Semi-additive Measures
Translations
User-defined Hierarchies
Writeback

26. Sources – Multidimensional
Access databases
SQL Server relational databases
Oracle relational databases
Teradata relational databases
Informix relational databases
IBM DB2 relational databases
Sybase Adaptive Server Enterprise (ASE) relational databases
Other relational databases
Text files
Microsoft Excel files
Power Pivot workbook
Analysis Services cube
Data feeds
Office Database Connection files

27. Sources – Multidimensional
Direct Query
Microsoft SQL Server
Microsoft Azure SQL Database
Microsoft Azure SQL Data Warehouse
Microsoft SQL Analytics Platform System (APS)
Oracle relational databases
Teradata relational databases

28. Sources – Tabular Access databases SQL Server relational databases
Oracle relational databases
Teradata relational databases
Informix relational databases
IBM DB2 relational databases
Sybase Adaptive Server Enterprise (ASE) relational databases
Other relational databases
Text files
Microsoft Excel files
Power Pivot workbook
Analysis Services cube
Data feeds
Office Database Connection files

29. Sources – Tabular Direct Query Access databases
SQL Server relational databases
Oracle relational databases
Teradata relational databases
Informix relational databases
IBM DB2 relational databases
Sybase Adaptive Server Enterprise (ASE) relational databases
Microsoft SQL Server
Microsoft Azure SQL Database
Microsoft Azure SQL Data Warehouse
Microsoft SQL Analytics Platform System (APS)

30. Links BI Semantic Model Multidimensional vs. Tabular Designing a Cube
Multidimensional vs. Tabular
models-for-sql-server-analysis-services/
Designing a Cube