1. DAX Gently Alnis Bajars. alnis@bajars.com @alnisb
A fast paced but sequential approach to learn
Data Analysis eXpressions
Alnis

2. Agenda
DAX Gently
Recap of Advantages of Power Pivot
Fundamentals of Power Pivot Environment
Calculated Columns
First Pivot Table ex Power Pivot
Calculated Fields aka Measures
Functions and their use
NOTE: Download Adventure Works DW 2014 (or recent version) to do the demos yourself.
Load FactInternetSales, selected Related Tables, select Product SubCat and Cat.

3. Assumptions So we don’t get bogged down.
Excel 2013 only (not 2010), and you can enable Power Pivot. (Note: Power BI Desktop emerging)
You know where Power Pivot fits into Power BI
You know the difference between Personal BI, Team BI and Corporate BI
You know the basic Power Pivot environment.
You know how to acquire data in Power Pivot
You understand the concept of the Data Model

4. Hot off the Press! Power BI Desktop coming July 24.
Power BI Designer Preview going live
Separates Power BI from Excel (corporate friendly)
No impediment to using 64 bit version
general-availability-coming-july-24th.aspx

5. References Power Pivot Succinctly by James Beresford DAX Patterns 2015
Best possible price
Great overview of Power Pivot ecosystem. Explains DAX well. Engine deep dive.
DAX Patterns 2015
By Marco Russo and Alberto Ferrari (The Italians)
Fast paced yet rigorous, does not over explain concepts
Other Books by the Italians
Ensure you have Power Pivot enabled. Excel 2013 or O365 preferred. Excel 2010 will work but UI quite different.
SQL Server 2012 Analysis Services: The BISIM Tabular Model
Excel 2013: Building Data Models with PowerPivot
Very rigorous and detailed, can be hard to digest
Books by Rob Collie, Bill Jelen, Kapser de Jonge
Widely available on Kindle. Some easy to digest explanations, lacks rigour in places

6. Advantages of Power Pivot
Recap
Advantages of Power Pivot

7. Advantages of Power Pivot
Breaks Excel 1 million row barrier
Fast and compressed xVelocity (ex Vertipaq), cf SSAS Tabular)
Eclectic range of data sources
Data modelling, no cell references
No Vlookup! The streets are safe again.
Can do a lot of things Excel formulas can’t easily do.
Prototype SSAS Tabular

8. And this is the focus of this presentation.
But be warned
Looks like simple Excel functions .. But be warned.
Mismatch of expectations by Microsoft
Subtleties of row context and filter context are not easy to master
Not necessarily a power user tool
And this is the focus of this presentation.
Fast track over the bleeding obvious and focus on the more challenging concepts.

9. Power Pivot Succinctly by James Beresford.
MDX vs DAX
Power Pivot Succinctly by James Beresford.

10. Power Pivot Environment
Fundamentals of
Power Pivot Environment

11. Getting Started Enable Power Pivot in Excel 2013.
Power Pivot: Switch to Advanced Mode

12. Demo: Relationships View
Free us from the tyranny of cells and Vlookups
Auto create known relationships
Manually create relationships
Cardinality is important: 1-many vs many-1
No direct support for many-many, simple workarounds later
Multiple relationships – but only one active (no direct role playing)

13. Demo: Hierarchies As per OLAP Create in Diagram View
Either drag drop members, or right mouse click

14. Data Manipulation Notes
Limited # of data types. Text, Decimal, Whole, Currency, TRUE/FALSE
Compression good, except for Decimal/Currency
Note BLANK() function. Behaviour not always obvious for arithmetic and Boolean.
DIVIDE function handles div by zero, optional parameter to override BLANK(). Cleaner code and performs better than IF.

15. Functions: The Bleeding Obvious

16. Demo: Cleanse Data
Delete columns not needed cf. Filter at Preview cf filter at data source
Helper columns not needed by user: Hide From Client Tools
Format columns

17. Demo: Mark as Date Table
Essential prerequisite for advanced time intelligence functions
Design -> Mark as Date Table
Nominate a Unique Column
Also sort Month Name by Month Number of Year

18. Calculated Columns vs Calculated Fields
Custom columns
Applies row by row , individual cells cannot be edited
By default, ROW CONTEXT
Calculated Fields
Called Measures in Excel 2010 (and Power BI Designer!)
Must be aggregates of some sort
By default, FILTER CONTEXT
Warning
Filters can be enforced, overridden or transitioned
Context must be understood to understand many of the powerful functions.
This is the KEY takeaway slide (hence Gold colour heading)..

19. Context Overview Row Context Filter Context Custom columns
Applies row by row
Individual
By default, ROW CONTEXT
Filter Context
Called Measures in Excel 2010
Must be aggregates of some sort
By default, FILTER CONTEXT

20. Calculated
Columns

21. Calculated Columns Basics
An extra column!
Format [Column Name] = <Formula>
Row Context
Applies row by row
See later contrasts with Filter Context
Table Qualification
Can use [Field Name]
Can use Table[Field Name} for disambiguation cf SQL

22. Demo: Calculated Columns
Note the ways to name the column
Note references to other columns cf. “official tables”
Note behavior of aggregations

23. Demo: Reference Other Tables
Premature look at first functions
RELATED() when direction from many to 1
RELATEDTABLE() when direction 1 to many
Will traverse relationships for as long as relationships of the same type
Sneak preview. CALCULATE auto works relationships 1-many

24. EARLIER Each pass of calculation engine creates a row context level
Acts like “CURRENTROW”, remembers previous row context
EARLIER(<column>, <skip_levels> )
skip_levels defaults to 1
Eg.
ListPriceRank
= COUNTROWS (
FILTER ( DimProduct,
DimProduct[ListPrice] > EARLIER ( DimProduct[ListPrice] )
)) + 1

25. First Pivot Table
From Power Pivot

26. Demo: Create Pivot Table
Note all tables visible, except “Hide From Client Tools”
Otherwise a lot like Pivot Tables … so far

27. Calculated Fields And Filter Context
Calculated Fields were called Measures in Excel 2010.

28. Demo: First Calculated Fields
Enter below the line
Note Pascal like assignment [Calculated Column] := <Formula>
Enter from Calculated Fields button
Note the default behaviour of filter context!

29. Aggregation Function Types
Standard Functions
AVERAGE, MAX, MIN, SUM
Can only pass one column as an argument
Append with A
AVERAGEA, MAXA, MINA
If text, returns 0 instead of error
Append with X
Solves the one column problem
<Function>X(Table, Expression)
SUMX( Sales, Sales[OrderQuantity] * Sales[UnitPrice] )
AVERAGEX, MAXX, MINX, SUMX

30. Count Functions COUNT, COUNTA COUNTX, COUNTAX COUNTBLANK COUNTROWS
COUNTDISTINCT

31. Essential Functions And their use
Covering the Functions that are the basis for common patterns.

32. FILTER Supply a table and filters
Returns table subset (cf. WHERE clause), still a table
FILTER(<table>, <filter1>, <filter2> …>
Eg.
SumHiValueProd :=
SUMX( FILTER(FactInternetSales, FactInternetSales[UnitPrice]>100),
FactInternetSales [OrderQuantity] * FactInternetSales [UnitPrice] )

33. CALCULATE Probably the most important DAX function
Roll your own filter context, including none at all
Still obeys active filters
CALCULATE(<expression>, <filter1>, <filter2> …>
Eg.
[Sales 2011] :=
CALCULATE ( SUM(FactInternetSales[SalesAmount]), DimDate[CalendarYear] = 2011)

34. ALL
Effectively removes filter each time a calculated field is executed
Eg.
[Sales 2011 ALL] :=
CALCULATE ( SUM(FactInternetSales[SalesAmount]), DimDate[CalendarYear] = 2011, ALL(DimDate))

35. HASONEVALUE
TRUE if current context filtered to just one value, otherwise FALSE
Eg.
[ResellerSales compared to 2011] :=
IF(HASONEVALUE(DateTime[CalendarYear]),
SUM(ResellerSales[SalesAmount])/
CALCULATE(SUM(ResellerSales[SalesAmount]),
DateTime[CalendarYear]=2011)
,BLANK())

36. USERELATIONSHIP
Make one of multiple relationships between tables active
Workaround for lack of support for role playing dimensions
Eg.
[Sales by Ship Date]
=CALCULATE(SUM(FactInternetSales[SalesAmount]), USERELATIONSHIP(FactInternetSales[ShipDateKey], DimDate[DateKey]))

37. First Look at Time Intelligence
Functions very difficult to do in Excel
Huge choice
Eg 1
[SalesYTD] :=
TOTALYTD( Sum(FactInternetSales[SalesAmount]), DimDate[FullDateAlternateKey] )
Eg 2
[PYSales] :=
CALCULATE(Sum(FactInternetSales[SalesAmount]),
SAMEPERIODLASTYEAR(DimDate[FullDateAlternateKey]) )

38. Many to Many Relationship
A number of workarounds, eg.
SUMMARIZE( Bridge_AccountNumber, DimAccount[ID_Account])

39. Summary Future Gently Talks Basic DAX simple and intuitive ….
But there are a lot of subtle tricks.
Lots of in depth material from The Italians
ie. Marco Russo and Alberto Ferrari
Future Gently Talks
If you think this format works well….
M Gently (Power Query)
R Gently (Machine Learning/ Predictive Analysis)
Alnis Bajars.