1. Modeling scenarios for DAX
Ana María Bisbé York
Business Intelligence Consultant
MS Partner on Power BI
@ambynet
Modeling scenarios for DAX

2. Thanks to all Sponsors

3. Say thanks to our volunteers
They spend their FREE time to give you this event.
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Because they want YOU to learn from the BEST IN THE WORLD.
João Sarmento
Eduardo Piairo
Diamantino Falcão

4. Agenda Intro Decisions to take: Evaluation context
Implicit vs Explicit Measures
Calculated columns vs measures
Measures vs Variables
Calculated columns vs Calculated Tables
Calculated columns vs Measures vs Context transition
Evaluation context
Definition
Test the quality of data
Modify current filter context

5. DAX - Introduction DAX – Data Analysis Expressions Tabular models
Power Pivot
SQL Server Analysis Services Tabular
Power BI
Functional language
Execution flows as function calls
From inner to outer most
Single line execution

6. Is it easy to write DAX expressions?

7. Demo !!! 

8. Is it easy to write DAX expressions?

9. Decisions to take !!

10. Calculated column vs Measures
Design of the model
Calculated column, (preferably during the Query step)
Headers of rows and/or columns of a table or matrix, discrete axis in charts or slicers
Measures (with DAX)
Examine the result as value, in the central panel of the pivot table
Use this value as data source for the KPI
Value depends on the user-defined context
Affected by table filters, charts and slicers

11. Explicit measures vs Columns
Implicit measures are created when a numeric column is selected.
The default aggregate function is Sum
Good practices:
Create the measure
It’s easier to read and to maintain the code
From them on, we can always select the Total Quantity measure.
We do not need the table name to refer to the measure, the measures belong to the model.
Explicit measures are wrapped in a CALCULATE, although we don’t write it
CALCULATE creates the transition from the row context into filter context.
This avoids the use of navigation functions, which once again improves reading and maintenance.
When exporting the model to Excel, the measures are available for the ”pivot table values”, numeric columns, in the other hand, are not.

12. Calculated columns vs measures
Two types of calculations in DAX
Calculated columns
It is evaluated row by row
It consumes more resources, calculates for every row of the column
Immediate calculation and storage in column of the tabular model
Useful for filters and segmentation.
Best Practices:
Creating calculated columns in a query.
Do not create calculated columns for numeric values
Measures
It is evaluated by using on a table/chart
It consumes less resources, only calculated for active elements.
Dynamic calculation, on the fly
Written always in DAX, same syntax, different context

13. Calculated columns vs measures
Calculations from columns Calculations from measures

14. Measures vs Variables Variables More readable code
Less evaluation for each function
No additional measure is created

15. Model types Unique table Snowflake Star
Excel classic, before Excel 2013
Snowflake
Normalized
There are links between the search tables
or directly to the facts tables.
Star
Denormalized model
All search tables (dimensions) point directly to the facts table

16. Relationships between tables and DAX
Combined filters from different tables All tables are pointing to Facts Tables

17. Relationships between tables and DAX
Crossfilter direction
Single direction in the model 
Need to filter in both directions 
Both directions in the calculation or in the model?

18. Relationships between tables and DAX
Crossed filter direction: bidirectional
The filter from Products propagates to Sales(1:M)
The filter propagates from Sales to Customers(M:1)
Caution – could be very dangerous 

19. Relationships between tables and DAX
Crossfilter direction
Single direction in the model
Both directions in the calculation !!
DAX to the rescue !!!

20. Calculated columns vs Calculated tables
Table with a single column Calculated column

21. Calculated columns vs Calculated tables
Tables created with columns, single DAX expression

22. Evaluation context

23. DAX Contexts Different results of a measure, depending on context
The result depends on:
The code
The filter context in which is evaluated

24. Testing context with FILTER
Given a context Create a temporary table to test the value Calculate the aggregated in a measurement

25. Testing context with FILTER
Given a context Calculate the aggregated of a measure, using directly the filter expression

26. Modifying context with DAX
Replace the existing FILTER context
With functions CALCULATE or CALCULATETABLE
Ignore existing context
With function ALL

27. Modifying context with DAX
Replace or Ignore existing context
Only when it corresponds
Analysis done by category
Nothing to replace or ignore ignorar

28. Modifying context with DAX
Contexts and comparisons
Compare in a single category
Exclude total value

29. Modifying context with DAX – April 2017
Quick measures – (preview versión)

30. Modifying context with DAX – Abril 2017
Surprise! Power BI Desktop writes DAX  Quick measures

31. Resources
Books Tools

32. DAX - Recap
It is easy to start writing DAX expressions for tabular models Very powerful, and delicate at the same time Measures and CALCULATE are our best allies #HappyDAXing 

33. Questions?
Ana María Bisbé York Thanks!!! #sqlsatPorto #sqlsat685