1. Implementing Common Business Calculations in DAX
Chris Webb

2. Who am I? Chris Webb (chris@crossjoin.co.uk)
Independent consultant specialising in Analysis Services and MDX (and PowerPivot and DAX!):
Blogger:
Author:
MDX Solutions 2nd Edition
Expert Cube Development With Analysis Services 2008

3. Agenda What is DAX and why should I learn it?
Calculated columns and calculated measures
Row context and filter context
Calculate()
Values()
Demos, demos, demos!

4. What is DAX? DAX is the new calculation language for PowerPivot
MDX is still the query language
It is a multidimensional calculation language like MDX, but the design goals were:
Make it easy to do common calculations (easier than MDX)
Make it easy to use for Excel power users, hence the Excel-based syntax
DAX expressions are limited to a single (though often very long) line of code

5. Why learn DAX?
Your power users will be learning it, and you’ll need to understand what’s going on in their PowerPivot models
It’s very likely that it will be used in future versions of SSAS – possibly as an alternative to MDX for some calculations
We love both DAX and MDX, and MDX is not going away. The challenge for us is to bring them together. We have some promising directions. That said – I think you’ll see DAX evolving in new important directions that MDX will never cover, and a large and growing portion of the calc work will be done in DAX. So my advice stands: all you guys need to become DAX gurus ASAP. Amir Netz, Microsoft

6. DAX Syntax and Functions
DAX syntax is based on Excel syntax
Only thing to watch out for is you need to use && and || for AND and OR
Supports around 80 Excel functions
Uses its own data types
In Excel you only have numbers or strings
Uses the concept of BLANK rather than NULL
PowerPivot BLANKs behave in exactly the same way as SSAS nulls
The UI for editing DAX is terrible – can use NotePad++ and Colin Banfield’s DAX language template instead

7. Referencing Columns and Measures
DAX usually requires fully qualified names, eg:
MyTable[MyColumn]
MyTable[MyMeasure]
You can use unqualified names in calculated column definitions, when referring to other columns in the same table
DAX cannot use standard Excel cell references to data elsewhere in the workbook.

8. Calculated Columns
DAX can be used to create two types of calculation: calculated columns and calculated measures
Calculated columns are derived columns in a PowerPivot table
Are defined inside the PowerPivot UI
After they are created, they behave like any other column
Their values are calculated immediately after the real data has been loaded into PowerPivot
Can be used to do basic ETL work, eg concatenating first and last names, deriving years from dates etc

9. Calculated Measures
Calculated measures provide the numeric values you see aggregated in pivot tables
All measures are calculated measures in PowerPivot!
Are defined within the pivot table in Excel
Are calculated at query time
Basic sum, count, min, max and average calculated measures can be created from the right-click menu
More advanced calculated measures can be created by entering your own DAX expression

10. Row Context and Filter Context
Row context refers to the current row where a calculation is taking place
There is no row context without a DAX aggregation function
Filter context refers to the currently selected item on each column on each table
Very similar to the CurrentMember function in MDX, but handles multiselect elegantly
Filter context follows the one-to-many relationships between tables
Both row and filter context must be taken into account when writing expressions for calculated measures

11. Row and Filter Context Examples

12. Filter Context

13. Filter Context

14. Row Context

15. Row Context with Calculation

16. Row Context with Calculation

17. Calculate()
The Calculate() function is the key to all advanced DAX calculation functionality
Signature: Calculate(Expression, SetFilter1, SetFilter2,...)
It allows any expression to be evaluated in a specific filter context
It works as follows:
Modifies the current filter context according to the SetFilter arguments you pass in
Shifts the row context onto the filter context
Evaluates your expression in the new filter context

18. Calculate() SetFilter arguments can either be:
Boolean expressions, eg CALCULATE(COUNTROWS(), Consultants[Skill]="MDX")
Table functions, so the filter context for any table is set to the rows returned by the table function, eg CALCULATE(COUNTROWS(), FILTER(Consultants, Consultants[Measure1]>3))
Useful table functions include:
Values(), which returns a list of distinct values in a column in the current filter context
All(), which returns a list of all the values in a column ignoring filter context

19. Ratio to All and Ratio to Parent
A common example of a ‘ratio to all’ and ‘ratio to parent’ calculations is a market shares
The numerator for this kind of calculation is easy: SUM('Consultants'[Measure1])
The denominator is the ‘all’ or ‘parent’ total
To get the total value of a measure with all filter context cleared we need to use All(Table), eg: CALCULATE(SUM('Consultants'[Measure1]), ALL(Consultants))
To get the total value of a measure with filter context for just one column removed, we need All(Column), eg: CALCULATE(SUM('Consultants'[Measure1]), ALL(Consultants[Consultant]))

20. Ratio to All and Ratio to Parent
This makes the final calculations:
=SUM('Consultants'[Measure1])/ CALCULATE(SUM('Consultants'[Measure1]), ALL(Consultants))
and
=SUM(Consultants[Measure1])/ CALCULATE(SUM('Consultants'[Measure1]), ALL(Consultants[Consultant]))

21. Previous Year Growth
Basic algorithm to calculate year-on-year growth is:
((Sales for Current Time Period) -
(Sales for Same Time Period in Previous Year)) /
(Sales for Same Time Period in Previous Year)
The big problem is how to calculate sales for the same time period in the previous year in the absence of SSAS-like hierarchies?

22. Previous Year Growth The following is the best approach:
=CALCULATE(SUM(FactInternetSales[SalesAmount]) , DATEADD(DimDate[FullDateAlternateKey], -1, YEAR) , ALL(DimDate))
Works by:
Finding all the dates in the current year
Shifting each date back one year
Setting this as the filter context
Summing SalesAmount for these dates
BUT will only give correct results if you have a complete set of dates in your year!

23. Previous Year Growth
Always a good idea in DAX to break complex calculations up into a series of simpler calculated measures
So, if we use the previous formula to define a calculated measure called Previous Year Sales, the growth calculation becomes:
=IF(FactInternetSales[Previous Year Sales]=0 , BLANK()
,(SUM(FactInternetSales[SalesAmount]) - FactInternetSales[Previous Year Sales]) / FactInternetSales[Previous Year Sales])
Notice, like in MDX, we need to trap division by zero

24. Rules for Time Intelligence functions
Five rules for using Time Intelligence functions:
Never use the datetime column from the fact table in time functions.
Always create a separate Time table, and make sure it contains complete years
Create relationships between fact tables and the Time table.
Make sure that relationships are based on a datetime column (and NOT based on another artificial key column).
The datetime column in the Time table should be at day granularity (without fractions of a day).

25. If you don’t follow the rules...
As we’ve already seen, not having complete years makes it hard to do relative time calculations
In my example, since I joined on a surrogate key and not a DateTime key, I needed to add All(DimDate) to my calculation
You can’t use RELATED() to bring the date down to the fact table either, because this causes a circular reference error!
Need to either alter the underlying relational table or view, or import the date dimension table twice

26. Year to Date
Luckily there are many built-in time intelligence functions for common calculations
Eg for doing year-to-date sums, we have TotalYTD:
=TOTALYTD( SUM(FactInternetSales[SalesAmount]) ,DimDate[FullDateAlternateKey] , ALL(DimDate))
In this case, TotalYTD is a variant of Calculate with some filters set automatically

27. Total to Date
A total-to-date gets the running total from the first date we have in our data
No built-in function for it
We need to use Calculate and set the filter to all dates from the first ever date to the last date in the current context
We can use DATESBETWEEN to get this date range
The first date can be got by using BLANK()
The last date with the LASTDATE() function

28. Total to Date The final version is: =CALCULATE(
SUM(FactInternetSales[SalesAmount])
, DATESBETWEEN('DimDate'[FullDateAlternateKey]
, BLANK()
, LASTDATE( 'DimDate'[FullDateAlternateKey]))
, All('DimDate'))

29. Values() – like CurrentMember but better!
The Values() function acts like the MDX CurrentMember function
But it is better: Values() returns a table, so it handles multiselect
Although when the table it returns only contains one row we can still do a direct comparison with another value
The Distinct() function works exactly the same way as Values() but:
Values() will return the Unknown Member
Distinct() will not

30. Distinct Count
To find a distinct count, we need to count the rows in a table containing only the distinct values from a column
The Values() function returns such a table
Because it’s a table, all we need to do is count the number of rows in it:
=COUNTROWS(VALUES(Consultants[Skill]))

31. Ranks There is no rank function in PowerPivot
So, for example if we wanted to calculate a rank for dates by sales, we would need to use the following approach:
For each date
Find a table containing the complete list of all dates
Filter that list of all dates to find those whose sales were higher
Count the number of rows in that table
Add 1

32. Ranks This gives as a first attempt: =COUNTROWS(
FILTER(ALL(DimDate[DateKey])
,(DimDate[DailySales](
VALUES(DimDate[DateKey]))
<
DimDate[DailySales]))) + 1

33. Rank only for Dates
With this knowledge, we can avoid doing the calculation when more than one date is in the row context:
=IF(
COUNTROWS(VALUES(DimDate[DateKey]))>1
, BLANK()
,COUNTROWS(
FILTER(ALL(DimDate[DateKey])
,(DimDate[DailySales](VALUES(DimDate[DateKey]))
<DimDate[DailySales]) )) + 1)

34. Time Utility dimensions in PowerPivot
Time Utility dimensions are an SSAS technique for applying one calculation to multiple measures
Also known as Date Tool or Shell dimensions
Since PowerPivot does not allow calculated members on anything other than the Measures dimension, it isn’t possible to create a true Time Utility dimension 
But... You can build something almost the same:
Create a calculated measure that allows you to select which real measure you want
Create a calculated measure that allows you to select which calculation you want, and apply it to the previous calculated measure

35. Final Thoughts DAX does the easy stuff very easily
DAX does the medium-hard stuff well too
Not sure if power users will get it, but
It’s easier than MDX
It’s more SQL-like, so more developers will get it
It’s more elegant than MDX in many ways, eg multiselect
DAX does not do the really hard stuff well at all
So for financial apps, for example, MDX still wins
But for how long?
I like DAX a lot

36. Links http://blogs.msdn.com/powerpivot/ http://www.powerpivot.com/

37. Thanks!

38. Coming up…
P/X001
How to Get Full Access to a Database Backup in 3 Minutes or Less
Idera
P/L001
End-to-end database development has arrived
Red Gate
P/L002
Weird, Deformed, and Grotesque –Horrors Stories from the World of IT
Quest
P/L005
Expert Query Analysis with SQL Sentry
SQLSentry
P/T007
Attunity Change Data Capture for SSIS
Attunity
#SQLBITS