Mastering DAX Video Course Information

This is the video course version of the Mastering DAX workshop.

DAX is the native language of Power BI, Power Pivot for Excel, and SSAS Tabular models in Microsoft SQL Server Analysis Services. The training is aimed at users of Power BI, Power Pivot for Excel, and at Analysis Services developers that want to learn and master the DAX language.

The goal of the course is to teach all the features of DAX, providing the knowledge to write formulas for common and advanced business scenarios. The video course is made up of over 15 hours of lectures, plus another 15-20 hours of individual exercises.

What You’ll Learn In Mastering DAX Video Course

Presentation of Mastering DAX 2nd Edition

• Presentation of Mastering DAX 2nd Edition

Exercises, labs, slides, and demos

• Exercises, labs, slides, and demos
• How to download and complete exercises
• Download exercises
• Download demos
• Slides of the video course

Introduction to DAX

• Introduction to DAX
• What is DAX?
• DAX data types
• Calculated columns
• Measures
• Aggregation functions
• Counting values
• Conditional functions
• Handling errors
• Using variables
• Mathematical functions
• Relational functions
• Exercises

Exercises solutions

• Exercises solutions
• 02.10 – Average sales per customer
• 02.20 – Average delivery time
• 02.50 – Last update of customer
• 02.40 – Working days
• 02.30 – Discount categories

Table functions

• Table functions
• Introduction to table functions
• Filtering a table
• Ignoring filters
• Mixing filters
• Distinct
• How many values for a column
• ALLSELECTED
• RELATEDTABLE
• Tables and relationships
• Tables with one row and one column
• Table variables
• Exercises

Exercises solutions

• Exercises solutions
• 03.20 – Percentage of sales
• 03.10 – Delivery working days
• 03.40 – Sales of products in the first week
• 03.30 – Customers with children

Evaluation contexts

• Evaluation contexts
• Introduction to evaluation contexts
• Filter context
• Row context
• Context errors
• Filtering a table
• Using RELATED in a row context
• Ranking by price
• Evaluation contexts and relationships
• Filters and relationships
• Exercises

Exercises solutions

• Exercises solutions
• 04.10 – Nested iterators
• 04.20 – Customers in North America
• 05.10 – Create a parameter table

The CALCULATE function

• The CALCULATE function
• CALCULATE
• CALCULATE examples
• CALCULATE recap
• What is a filter context?
• KEEPFILTERS
• CALCULATE operators
• Use one column only in compact syntax
• Variables and evaluation contexts
• Exercises

Exercises solutions

• Exercises solutions
• 05.05 – Sales of red and blue products
• 05.20 – Understanding CALCULATE
• 05.25 – Sales of blue products
• 05.15 – Computing percentages

Advanced evaluation contexts

• Advanced evaluation contexts
• CALCULATE modifiers
• USERELATIONSHIP
• CROSSFILTER
• ALL
• ALLSELECTED
• KEEPFILTERS
• Context transition
• Context transition /2
• Circular dependency
• CALCULATE execution order
• Exercises

Exercises solutions

• Exercises solutions
• 05.35 – Correct sales of grey products
• 05.40 – Best customers
• 05.45 – Customers buying many products
• 05.50 – Large sales
• 05.30 – Percentage of customers
• 05.55 – Counting spikes

Iterators

• Iterators
• Working with iterators
• MINX and MAXX
• Useful iterators
• RANKX
• ISINSCOPE
• Exercises

Exercises solutions

• Exercises solutions
• 07.10 – Ranking customers (static)
• 07.20 – Ranking customers (dynamic)
• 07.30 – Date with the highest sales
• 07.40 – Moving average
• Building a date table
• Building a date table
• Introduction to date table
• Auto Date/Time
• CALENDARAUTO
• Mark as date table
• Using multiple dates

Time intelligence in DAX

• Time intelligence in DAX
• What is time intelligence?
• Time intelligence functions
• DATEADD
• DATESINPERIOD
• Running total
• Mixing time intelligence functions
• Semi-additive measures
• Calculations over weeks
• Exercises

Exercises solutions

• Exercises solutions
• 08.10 – Running total
• 08.20 – Comparison YOY%
• 08.30 – Sales in first three months
• 08.40 – Semi-additive calculations
• Hierarchies in DAX
• Hierarchies in DAX
• What are hierarchies?
• FILTER and CROSSFILTER
• Percentages over hierarchies
• Parent-child hierarchies

Querying with DAX

• Querying with DAX
• Working with tables and queries
• EVALUATE
• CALCULATETABLE
• SELECTCOLUMNS
• SUMMARIZE
• SUMMARIZECOLUMNS
• CROSSJOIN
• TOPN and GENERATE
• ROW and DATATABLE
• Tables and relationships
• UNION, INTERSECT, and EXCEPT
• GROUPBY
• Query measures
• Exercises

Exercises solutions

• Exercises solutions
• 13.10 – Sales by year
• 13.20 – Filtering and grouping sales
• 13.30 – Using TOPN and GENERATE
• 13.40 – Sales to top customers
• 13.50 – Sales of top three colors

Data lineage and TREATAS

• Data lineage and TREATAS
• What is data lineage?
• TREATAS

Expanded tables

• Expanded tables
• Filters are tables
• Difference between base tables and expanded tables
• Filtering a column
• Exercises

Exercises solutions

• Exercises solutions
• 14.10 – Distinct count of countries
• 14.20 – Sales quantity greater than two

Arbitrarily shaped filters

• Arbitrarily shaped filters
• What are arbitrarily shaped filters?
• Example of an arbitrarily shaped filter

ALLSELECTED and shadow filter contexts

• ALLSELECTED and shadow filter contexts
• ALLSELECTED
• Shadow filter contexts
• Segmentation
• Segmentation
• Static segmentation
• Circular dependency in calculated tables
• Dynamic segmentation
• Exercises

Exercises solutions

• Exercises solutions
• 15.10 – Static segmentation

Many-to-many relationships

• Many-to-many relationships
• How to handle many-to-many relationships
• Bidirectional filtering
• Expanded table filtering
• Comparison of the different techniques
• Exercises

Exercises solutions

• Exercises solutions
• 15.30 – Many-to-many relationships

Ambiguity and bidirectional filters

• Ambiguity and bidirectional filters
• Understanding ambiguity

Relationships at different granularities

• Relationships at different granularities
• Working at different granularity
• Using TREATAS
• Calculated tables to slice dimensions
• Leveraging weak relationships
• Scenario recap
• Checking granularity in the report
• Hiding or reallocating
• Additional exercises
• Exercises

Exercises solutions

• Exercises solutions
• 14.30 – Same product sales
• 14.40 – Commentary on report
• 15.20 – New customers

Calculation groups

• Calculation groups
• Introducing calculation groups
• Basic measures
• Calculation items are patterns
• Creating calculation groups
• Changing the format string
• Excluding specific measures
• Using calculation items in DAX
• Calculation item application
• Calculation items on complex expressions
• Multiple calculation groups in a report
• Understanding precedence in calculation groups
• Reusing calculation items
• Recursion and best practices
• Exercises

Exercises solutions

• Exercises solutions
• 09.10 – Time calculations
• 09.20 – Multiple calculation groups
• 09.30 – Sold versus delivered
• 09.40 – Min, Max and Avg calculation group
• 09.50 – Top and bottom products
• STUDENT RATING

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