Power BI, SSAS Tabular, and Excel all use DAX. This presentation is meant to be used with a PBIX notebook found here: https://github.com/IkeEllis/democode/blob/master/IntroToDAX/Power%20BI%20Introduction%20to%20DAX.pbix

1. Introduction to DAX
Ike Ellis, MVP
Crafting Bytes
@ike_ellis
ike@craftingbytes.com
www.ikeellis.com

2. Do you know DAX?

3. What do you need to know in order to say yes, I know DAX?
1. You need to know these functions:
• SUM, AVERAGE, MIN, MAX
• COUNT, COUNTROWS
• CALCULATE
• FILTER
• IF/VARIABLES
2. You need to know about Contexts
• Row Context
• Filter Context
3. Some other things:
• Formatting
• White space
• Time intelligence
• Best Practices
• X vs nonX functions(SUM vs SUMX)
• DAX Studio
• Basic Troubleshooting

4. So how will you learn it?
• Go in order:
• This slide deck
• This Power BI Project
• Practice, practice, practice

5. And how will you use it?
• Works in Excel
• Works in Power BI
• Works in SQL Server Analysis Services (SSAS) Tabular

6. This presentation
• Simplifies the complexity
• Might not tell you the whole truth for the sake of simplicity
• Is not seeking to be comprehensive, but instead, seeks to allow you to
answer the question, yes, I know DAX in that job interview

7. Your first DAX expression
• Check Power BI Desktop tab “Your First DAX Expression”
• It’s a calculated column called Order Line Total
• Meant to add a column to every record in a table.
Order Line Total = 'Sales OrderDetails'[qty] * 'Sales OrderDetails'[unitprice]

8. Your Second DAX Expression
• Check Power BI Desktop tab “Your Second DAX Expression”
• This is a measure
• Meant to perform an aggregation that we can slice & dice
Total Sales = SUM('Sales OrderDetails'[Order Line Total])

9. How can we verify this?
select sum(Sales.OrderDetails.unitprice * Sales.OrderDetails.qty)
from sales.OrderDetails

10. DAX Expression Breakdown
Name the
measure.
You’ll use
that in the
visualization
Built in DAX formula
Table name
Column nameEquals sign separates
expression name from
expression formula
Total Sales = SUM('Sales OrderDetails'[Order Line Total])

11. All kinds of easy to use DAX formulas that you can learn
quickly
• SUM
• AVERAGE
• MIN
• MAX
• COUNT
• COUNTROWS
• DATEDIFF
• DATEADD

12. • Look at tab “Easy DAX built-in formulas”
• Look under the Orders table for the calculated column “Days to Ship”
• Look under Orders table for measure “Average Days to Ship
Days To Ship = DATEDIFF('Sales Orders'[orderdate], 'Sales Orders'[shippeddate],DAY)
Play again: AVERAGE and DATEDIFF
Average Days to Ship = AVERAGE('Sales Orders'[Days To Ship])

13. Your Third DAX expression: Calculated Table
• Look at the Dates table. It was built with a DAX expression
• Created a Dates table with a date per day between the specified
range
• Also created a Dates hierarchy
Dates = CALENDAR("1/1/2000", "12/31/2016")

14. Now on to Contexts!
• Two different contexts:
• Row Context
• Filter Context

15. Row Context
• We already know how this works! We’ve been using it for all of our calculated
columns. Let’s revisit our first DAX Expression
• Notice we expect a value per row in a table
• This runs at import and gets stored
• Might increase file size
Order Line Total = 'Sales OrderDetails'[qty] * 'Sales OrderDetails'[unitprice]

16. Filter Context
• Easy to show with measures
• Look at Filter Context 1, 2, 3 in the Power BI Desktop file (PBIX).

17. Filter Context 1
• We see it filtered by year and optionally by product category
• The measure is only defined once, and the DAX engine takes care of doing
the calculations on the fly
• The calculations are not stored, but created and retrieved at query time

18. Filter Context 2
Total Sales by year and with a page filter.

19. Filter Context 3
• Visuals can impact each other and change context

20. Now that we understand context, we can answer
this: Measures vs Calculated Columns
Measures Calculated Columns
Different functions Uses Row Contex
Doesn’t take up space Mostly text
Less space Executes at the point data is read into the model and
saved (value is static)
Filter Context
Executed at the time it is used

21. CALCULATE: Breaking out of the filter context
Beverages Total Sales = CALCULATE
(
SUM('Sales OrderDetails'[Order Line Total])
, 'Production Categories'[categoryname] = "Beverages"
)
AGGREGATION
FILTER
Look at the tab CALCULATE

22. FILTER
Number of Orders = COUNT('Sales Orders'[orderid])
Number of US Orders = CALCULATE
(
COUNT
(
'Sales OrderDetails'[orderid]
)
, FILTER
(
'Sales Customers'
, 'Sales Customers'[country] = "USA"
)
)

23. VARIABLES & RETURN
Total Sales For Customers with Minimum Order Count =
VAR MinimumOrderCount = 5
VAR CustomersWithMinimumOrders = CALCULATE
(
sum('Sales OrderDetails'[Order Line Total])
, FILTER('Sales Customers', [Number of Orders] > MinimumOrderCount)
)
RETURN CustomersWithMinimumOrders

24. Variables
VAR myVar = 1
Data Type Variable
Name
Variable
Value
RETURN myVar + 25
Expressions must use RETURN to return a value

25. Debugging using variables
• RETURN does not need to return the last variable
• In a multi-step formula, you can return an earlier value to
troubleshoot it
• Simplifies the reading of code, rather than endlessly nesting values
over and over again.

26. Time Intelligence: TOTALYTD
YTD Total Sales = TOTALYTD
(
SUM('Sales OrderDetails'[Order Line Total])
, Dates[Date].[Date]
)

27. Time Intelligence: PREVIOUSMONTH
Total Sales Previous Month = CALCULATE
(
sum('Sales OrderDetails'[Order Line Total])
, PREVIOUSMONTH(Dates[Date])
)

28. X vs nonX functions(SUM vs SUMX)
• SUM is an aggregator function. It works like a measure, calculating
based on the current filter context.
• SUMX is an iterator function. It works row by row. SUMX has
awareness of rows in a table, hince can reference the intersection of
each row with any columns in the table.

29. SUM vs SUMX Example
Total Sales SUMX = SUMX(
'Sales OrderDetails'
, 'Sales OrderDetails'[qty] * 'Sales OrderDetails'[unitprice]
)
Total Sales = SUM('Sales OrderDetails'[Order Line Total])

30. Best Practice: Organize your code
• Keep measures together
• Organize them by type
• Simple aggregation
• Time variance
• Ratios and differences
• Business-specific calculations

31. Best Practice: Naming Columns & Measures
• Feel free to use spaces
• Avoid acronyms
• Make names terse, but descriptive
• Makes Q & A easier to use
• In formulas, reference table names for calculated columns and do not
reference table names for measures, so you’ll know the difference

32. Best Practice: Formatting
• DAX Expressions can have lots of parentheses and square brackets
• Please use white space to control this
• Here’s an example of a properly formatted calculated column
Days To Ship = DATEDIFF
(
'Sales Orders'[orderdate]
, 'Sales Orders'[shippeddate]
, DAY
)

33. Basic Troubleshooting
• A lot of things can go wrong, but the problem is usually one of two things:
1. A relationship is misconfigured or the data is wrong in the model.
2. Wrong data type

34. Data types
• Numeric
• String
• Bool
• DateTime
• If a function is expecting a numeric, but gets a string, it won’t work.
Clean up the model and watch it start working.
• Uses less space and memory with your model
• Improves performance

35. Relationships

36. Manipulating the relationships
Total Sales By Ship Year = CALCULATE
(
SUM('Sales OrderDetails'[Order Line Total])
, USERELATIONSHIP('Sales Orders'[shippeddate], Dates[Date])
)
Only one active relationship at a time

37. DAX Studio
• Parses
• Formats
• Shows execution plan
• Connects to SSAS Tabular or
Power BI Desktop

38. Other Resources

39. Contact Me!
http://www.craftingbytes.com
http://blog.ikeellis.com
http://www.ikeellis.com
YouTube
http://www.youtube.com/user/IkeEllisData
San Diego Tech Immersion Group
http://www.sdtig.com
Twitter: @ike_ellis
619.922.9801
ike@craftingbytes.com