An introductory session to DAX and common analytic patterns that we've built and used in enterprise environments. This session was originally presented at SQL Saturday Silicon Valley 2016.

1. Intro to DAX Patterns

2.  Eric Bragas – MCP, PSM I
 DesignMind - Business Intelligence Consultant

3. Agenda
 DAX
 Data Analysis Expressions
 Notation
 Functions
 Evaluation Contexts
 Measure Patterns
 Calculated Column Patterns

4. Data Analysis Expressions (DAX)
 What is DAX?
 DAX is a language that allows us to write dynamic expressions for relataional
constructs, using familiar functions
 Powerful dynamic data analysis tool for relational data
 Expressions can traverse relationships!
 Available in PowerPivot, PowerBI, and SSAS Tabular
 Classic “Import Mode”
 What isn’t DAX?
 NOT a programming language

5. DAX Notation
Table
‘Table’
Column
‘Table’[Column]
Function
fn ( <arguments> )
Measure
Measure Name := SUM ( ‘Table’[Column] )
Calculated Column
Column Name = SUM ( ‘Table’[Column] )

6. Measures
 A measure is a formula/expression comprising functions applied to
columns and tables
 Reusable aggregation evaluated differently, depending on how you use it
 Measures can be nested

7. Functions
 Logical
 IF( logical test, <value if true>, <value if false> )
 SWITCH( <expression>, <value>, <result>, … ) – evaluates an expression against a list of values, and returns the result corresponding to the first matching value
 TRUE() – returns logical true
 Aggregate
 SUM( <column> ) – adds all the numbers in a column
 DIVIDE( <numerator>, <denominator>, [, <alternateresult>] ) – basic division; optional value returned
 Statistical
 MAX( <column> ) – returns the largest numeric value in a <column>
 MIN( <column> ) – returns the smallest value in a <column>
 Text
 BLANK() – returns a blank
 Filter
 FILTER(<table>, <filter>) – returns a table representing a subset of another table or expression
 ALL( <table> | <column>) – returns all the rows in a table, ignoring any filter context
 VALUES(<table or column>) – returns one column of the distinct values from the specified column or table
 CALCULATE( <expression>, <filter1>, <filter2>, … ) – evaluates an expression in a context that is modified by the specified filters

8. Functions (cont’d)
 Date and Time
 TODAY() – returns the current date
 NOW() – returns the current date and time in datetime format
 Time Intelligence*
 DATESBETWEEN(<dates>, <start date>, <end date>) – returns a table of <dates> starting with the <start date> and continues
until the <end date>.
 NEXTDAY(<dates>) – returns a table that contains a column with the next dates following each of the <dates> passed
 FIRSTDATE(<dates>) – returns the first date in the context of the specified column of dates
 LASTDATE(<dates>) – returns the last date in the context of the specified column of dates
 SAMEPERIODLASTYEAR(<dates>) – returns a table with a column of dates shifted one year back for each of the <dates> specified
 LASTNONBLANK( <column>, <expression> ) – returns last value in the <column> where the <expression> returns blank
 FIRSTNONBLANK( <column>, <expression> ) – returns the first value in the <column> where the <expression> returns blank
*Requires Date Table

9. Evaluation Contexts
 Evaluation Contexts:
 Filter Context
 Four types of filter context:
1. Row Selection
2. Column Selection
3. Slicer Selection
4. Filter Selection
 Defines the subset of data a measure is calculated using aka “Which rows are selected based on which attribute
values?”
 Applied before anything else
 Row Context
 All the columns in the Current Row
“DAX is simple, it’s not easy, but it’s
simple”
- Alberto Ferrari

10. Basic Evaluation Context - Demo
TotalSales = SUM ( Sales[SalesAmount] )

11. Anatomy of a Filter Context -
PivotTable
Rows
Slicer

12. Anatomy of a Filter Context - Chart
Filter
Slicer

13. Measure Patterns
BASIC
CUMULATIVE
YTD
YEAR OVER YEAR
SEMI-ADDITIVE
DISCONNECTED SLICERS

14. Basic Measures
 SUM( ‘Sales’[SalesAmount] )
 AVERAGE( ‘Inventory’[InventoryOnHand] )
 MIN( ‘Weather’[Temp] )
 MAX ( ‘Weather’[Temp] )
 Etc.

15. Basic Measure Demo – PowerPivot &
PowerBI
Asia Sales :=
CALCULATE ( [Total Sales],
Geography[ContinentName] = "Asia" )
Asia Sales :=
CALCULATE (
[Total Sales],
FILTER ( 'Geography',
Geography[ContinentName] = "Asia" )
)
Boolean
Table

16. Cumulative Total Measures
 Aggregates values of a column for the currently selected date and all previous dates within
the specified range
 Can be used to derive balances from transactions eg.
 Inventory Stock
 Balances
 Cumulative Balances
 Does not require use of Time Intelligence functions

17. Cumulative Measure Demo - PowerBI
Cumulative Energy Generated (Checked) =
IF (
MIN ( 'Date'[Date] ) <= MAX ( ‘Output’[Date], ALL ( ‘Output’ ) ) ,
CALCULATE (
SUM ( 'Output'[Energy Generated] ),
FILTER ( ALL ( 'Date'[Date] ), 'Date'[Date] <= MAX ( 'Date'[Date] ) )
)
)

18. Year-to-Date Total
 TOTALYTD function applies the expression for all data from the start of the year to the
currently selected date in the filter context
Year To Date =
TOTALYTD( <expression>, <dates> [, <filter>] [, <year end date>] )

19. Year-to-Date Total Demo - PowerBI
Total Energy Generated YTD =
TOTALYTD ( SUM ( 'Output'[Energy Generated] ), 'Date'[Date] )

20. Year Over Year
 Use time intelligence to calculate an aggregate for the same period last year
 “Last Year” measure is used to compare to “Current Year” measure, and/or to derive a
measure of the change year-over-year

21. Year-Over-Year Demo – PowerBI
Total Energy Generated Last Year =
CALCULATE ( [Total Energy Generated], SAMEPERIODLASTYEAR ( 'Date'[Date] ) )

22. Semi-Additive Measures
 Snapshot Fact Table with balance values, such as Inventory or
Account Balances
 These scenarios disallow us from summing across time
 The solution is to sum across all attributes except for time by
filtering for only a single point in time (eg. last date in the period)
 Several functions allow you to adjust filter context to a single
point in time, within the original context period
 FIRSTDATE / LASTDATE
 FIRSTNONBLANK / LASTNONBLANK
 OPENING… / CLOSING…

23. Semi-Additive Measure Demo -
PowerPivot
Total On Hand Quantity LASTNONBLANK =
CALCULATE (
SUM ( Inventory[OnHandQuantity] ),
LASTNONBLANK ( 'Date'[Date],
CALCULATE ( SUM ( Inventory[OnHandQuantity] ) ) )
)

24. Disconnected Slicers
Allows you to use a slicer to modify measures
 Measure Switching
 Used to switch between a set of measure values in a container measure

25. Disconnected Slicers Demo - PowerBI
Setup Steps:
1. Create/identify your target measures (eg. [Energy Exported] & [Energy
Generated])
2. Create disconnected table to use in slicer selection
3. Create background “value selection measure” using MAX()
• Hide this!
4. Create SWITCH measure to use in visualizations

26. Calculated Column
Patterns
VALUE BINNING

27. Value Binning
 Used to group similar values, or to bin values for
analysis aka Histograms
 Can bin values based on equality, or inequality
comparisons with the SWITCH() function
 Use Cases:
 Age groups
 Product Groups
 Any kind of frequency distributions

28. Value Binning Demo - PowerBI
Inventory Age (bin) =
SWITCH (
TRUE (),
'Inventory'[DaysInStock] < 20, "0-20",
'Inventory'[DaysInStock] < 50, "21-50",
'Inventory'[DaysInStock] < 80, "51-80",
'Inventory'[DaysInStock] < 100, "81-100",
"101+"
)

29. Summary
 DAX is dynamic because you can write measures that correctly evaluate under
their current Evaluation Context
 Filter Context
 Row Context
 Functions are the building blocks of our measures and perform a myriad of
tasks eg. altering Context, aggregating, logical operations, time intelligence,
etc
 Time Intelligence functions require a Date table to operate
 Understanding Tabular Data Modeling will go a long way towards helping your
understanding of DAX

30. Thanks!