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Exploring the Essential Features of “Sqlbi – Mastering DAX Video Course”
Mastering DAX Video Course
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. You can watch the videos at anytime and the system will keep track of your progress. Within the course you can download the material for all the exercises.
Students have access to a private discussion area where they can interact with the instructors asking questions related to the lectures and the exercises.
Curriculum
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
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