1. Cubes for Flat Table Land
Michael P. Antonovich
#SharePointMikeA

2. My Published Books Speaker at:
User’s Guide to the Apple ][
FoxPro 2 Programming Guide – 1992
Debugging and Maintaining FoxPro – 1992
Using Visual FoxPro 3.0 – 1995
Using Visual FoxPro 5.0 – 1996
Office and SharePoint User’s Guide – 2007
Office and SharePoint User’s Guide – 2010
Speaker at:
Code Camp 2009, 2010, 2011, 2012 Orlando
SharePoint Saturday 2011 & 2012 Tampa, 2012 Orlando
SQL Saturday - #1, #4, #8, #10, #15, #16, #21, #32, #38, #49, #62, #74, #79, #85, #86, #110, #130, #151, #168
IT PRCamp – Jacksonville 2012
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October 24, 2012

3. Some Basic BI Terminology
IMPORTANT BI TERMS
Aggregate
A mathematical function that allows you to summarize values of an attribute
Dimension
A dimension is essentially a look-up table that may define a hierarchy or drill-down path such as Year > Quarter > Month
Measure
A measure is something that identifies a value
Fact
A fact is another term for a measure that contains numeric data that can be grouped along one or more dimensional hierarchy
Star Schema
All dimension tables radiate out from a single fact table
Snowflake Schema
One fact table may relate to another fact table before relating to dimension tables. One dimension table can also have a related dimension table
A Pivot table or chart is usually based around a single fact table
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4. Two Models in SSAS Multidimensional Model Tabular Model
No major functionality changes since 2008 R2
Tabular Model
Visually and functionally resembles PowerPivot 2012
Both can be installed as separate instances on the same server.
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5. Advantages of the MultiDimensional Model
Tested technology since SQL 2000
Pre-calculated aggregates provide performance enhancements.
Can handle larger data since it can store data on disk (MOLAP) or directly query the relational data source (ROLAP)
Uses MDX which is supported by many 3rd party client tools.
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6. Disadvantages of the MultiDimensional Model
Model is getting ‘old’ and is not being revised. (designed for 32 bit, row based data and disk storage).
MDX is perceived as being difficult to learn.
Processing a multidimensional model can result in substantial downtime for large models.
Changes to one table require the entire model to be reprocessed.
Not compatible with PowerPivot
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7. Advantages of the Tabular Model
A 100% memory-based model provides greater performance.
The xVelocity analytics column based engine offers significant query performance improvements.
Queries and formulas use DAX which is ‘easier’ to learn than MDX. (MDX is also supported)
Queries data from many different data sources.
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8. Disadvantages of the Tabular Model
Does not support many-to-many relationships.
Does not support true role-playing dimensions.
Does not support cell-level security.
Does not support security on measures.
Does not support translations of metadata for locales.
Does not support ragged hierarchies.
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9. Which to Choose?
For most applications (60-70%) either model will work.
Do you currently have a model in Multidimensional mode?
Are you just learning Analysis Services?
Licensing issues?
Compatibility with PowerPivot?
Hardware?
Performance Issues?
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10. SSAS Tabular Uses DAX DAX Stands for Data Analysis Expressions
DAX is used to:
Create calculated columns
Create custom measures
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11. Basic Syntax DAX Data Types DAX Operators Integer Real Currency
DAX expressions always begin with an equal sign: =
Column References can be qualified or unqualified
TableName[ColumnName]
[ColumnName]
DAX Data Types
DAX Operators
Integer
Real
Currency
Date(DateTime)
TRUE/FALSE (Boolean)
Text
+, -
*, /
=, <>
>,<
>=, <=
&
AND &&
OR ||
NOT !
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12. DAX Functions 2010 Version consisted of 135 functions
71 functions are similar to Excel functions
69 have the same name – 2 do not
TEXT  FORMAT
DATEDIF  YEARFRAC
64 functions are unique to DAX
Aggregate data functions
Date related functions
2012 Version has a little over 170 functions (no, I will not cover them all today)
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13. Types of DAX Calculations
Simple Calculations
Calculated columns within fact tables
Calculated columns for dimension tables
Calculated columns between tables
Calculated columns to eliminate lookup tables
Calculated columns to serve as links to tables using multiple columns
(Calculated columns are calculated for every row in the table) Context is the row
Aggregate Calculations
Calculate unique measures
Context is in the evaluation of the pivot data
(Aggregate measures are only calculated for the displayed data in the Pivot table)
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14. Tabular Model Can Import From
Microsoft Access 2003, 2007, 2010
Microsoft SQL Server 2005, 2008, R2
Oracle Relational DB 9i, 10g, 11g
Teradata V2R6, V12
IBM Relational Database 8.1
Sybase Relational Databases
Many other ODBC Databases
Text files (.txt, .tab, .csv)
Analysis Services Cubes from SQL Server
Data Feeds using Atom 1.0 Format
Excel Files from , 2007, 2010
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15. Demo 1a: Retrieve Data from Multiple Sources
Open C:\Contoso2012\Stores.xlsx and rename to C:\Contoso2012\SQLSaturday1.xlsx
Go to PowerPivot window and load SQL Server database: Contoso2012 using all tables
Add to Data Model, Stores from the current spreadsheet. This is a linked table.
Add Access database ProductCategories.
Add Excel file: Geography.xlsx
Use the following data sources:
Open C:\Contoso2012\Stores.xlsx and rename to C:\Contoso2012\SQLSaturday1.xlsx
Go to PowerPivot window and load SQL Server database: Contoso2012 using all tables
Add to Data Model, Stores from the current spreadsheet. This is a linked table.
Add Access database ProductCategories.
Add Excel file: Geography.xlsx
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16. Demo 1a: Load Data
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17. Loading Data into the Tabular Model
Demo
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18. Demo 1b: Create Relationships
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19. Demo 1c: Show Diagram View
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20. Creating Relations Between Tables
Demo
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21. Technical vs. Useless Columns
Technical Columns
Used to link tables (IDs)
Use to calculate other columns
Hide from Pivot Table Field List
Useless Columns
Came in when data imported from data source
Not used in pivot table or to link tables
Delete to improve performance
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22. Demo 2: Eliminate Useless Columns and Hide Technical Columns
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23. Denormalize Data Model
Eliminate tables and columns that are not going to be used.
Flatten structure by created calculated dimension attributes based on values in other tables.
Hide columns used in calculations but which users no longer need to see.
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24. Create a Hierarchy Predefine common hierarchies for users
Hierarchies are defined from the largest grouping to the smallest:
Product Category
Product Subcategory
Product
After defining the hierarchy, you can remove the individual columns used to define the hierarchy.
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25. Demo 3: Define a Product Hierarchy
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26. Demo 4: Demo of Cube (so far) Using Excel Pivot
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27. Building Hierarchies
Demo
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28. Create a Calculated Measure
For those times when a built-in measure just isn’t enough… …you need a custom measure creating using DAX to satisfy the need. What is new in 2012 is that calculated measures can now be defined in the calculation area of the fact table.
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29. Creating Custom DAX Measures
For example, suppose you want to display the percent increase or decrease in sales by product in your stores channel for this year vs last year.
You need a new measure to calculate store sales:
StoreSales:=CALCULATE(SUM([SalesAmount]),DimChannel[Ch annelName]="Store")
By default, the above calculates sales for the entire table. However, in the pivot table, we can use the dimension: YEAR as a filter or slicer to perform the calculation by each year in the table.
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30. Dimensions Serve as Filters
Use Time Functions to calculate measures for other time periods.
LastYrSales:=CALCULATE([StoreSales],
DATEADD(DimDate[Datekey],-1,year))
The above expression allows us to reference an existing expression but apply an additional filter to the calculation of StoreSales (which is already filtering on the channel: store). That additional filter in this case calculates the Store sales for the date one year prior to the current date of the record.
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31. Calculate the Percent Change in Sales
Given the prior two calculated measures, store sales for the current year and store sales for the prior year for each period in the cube, you can now calculate the percent change using an expression like:
YearlyGrowth:=([StoreSales]-[LastYrSales])/[LastYrSales]
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32. Using Error Checking
Actually, the above sample works only because the slicer limited the calculations to specific years. However, in general, you need to check equations for error conditions like dividing by zero by using a formula more like: YearlyGrowth:=IF(ISBLANK([StoreSales]) || ISBLANK([LastYrSales]), 0, ([StoreSales]- [LastYrSales])/[LastYrSales])
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33. Demo 5a: Define a Calculated Measure
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34. Demo 5b: The Pivot Table with Calculated Measures
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35. Turning a Calculated Measure into a KPI
KPI are nothing more than calculated measures in a fact table that are compared to a target value to determine whether the value is good or bad.
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36. Adding KPI Calculations
What is a KPI?
Key
Performance
Indicator
Key Performance Indicators provide information at a glance to indicate status of a measureable fact about your company/organization
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37. Adding KPI Calculations
A KPI Needs:
A Base Value
A Target Value
A number of status intervals
Thresholds for each interval
Symbols to use to indicate status
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38. Demo 6a: Using DAX to Create a KPI
C:SQLSaturday/DAX/Vaccinations2Time
=COUNTROWS(DISTINCT(Patient_Vaccinations[VisitID]))
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39. Demo 6b: Using DAX to Create a KPI
C:SQLSaturday/DAX/Vaccinations2Time
=COUNTROWS(DISTINCT(Patient_Vaccinations[VisitID]))
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40. Adding a KPI
Demo
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41. Sorting by Other Fields
You notice in the previous demo that while the rows displayed the sales by month, the months were sorted alphabetically, not chronologically.
No one will accept that.
How can you sort the months correctly.
PowerPivot 2012 introduces a Sort by Another Column feature!
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42. Define a Calculated Column with the Month #
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43. Associate the Month Label with the New Column
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44. Demo 6c: Correctly Ordered Months
C:SQLSaturday/DAX/Vaccinations2Time
=COUNTROWS(DISTINCT(Patient_Vaccinations[VisitID]))
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45. Sorting on Alternate Columns
Demo
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46. Useful Links
My blog is running a series of articles on working with the Tabular model
Using the SSAS Tabular Model Week 1
Gathering Data From Different Data Sources Week 2
Displaying your first Pivot Table from a Tabular Model
Hierarchies
KPIs
Clean-Up in Week 7
DAX On-line Function Reference
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47. Got Questions?
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48. Thank You Michael P. Antonovich Mike@micmin.org Blog site:
Don’t forget your evaluations.
Michael P. Antonovich
Blog site:
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October 24, 2012