Data modeling is a required skill to get the best out of Power BI, Power Pivot for Excel, and Analysis Services. This video course is aimed at users of Power BI Desktop or Power Pivot for Excel, and at Analysis Services developers who want to learn how to build the optimal data model for their reporting needs.
The goal of the course is to teach through examples of increasing complexity how to solve business scenarios by adapting the data model, so that the required DAX code becomes easier, faster and more robust. All the demos and the exercises are based on Power BI examples. However, the very same concepts can be applied to Power Pivot and Analysis Services Tabular.
The course is made of more than 10 hours of lectures, and other 8 hours of individual exercises. You can watch the videos at any time and the system will keep track of your advances. Within the course you can download the material for all the exercises.
Presentation of Data Modeling for Power BI
Presentation of Data Modeling for Power BI FREE
- Presentation of Data Modeling for Power BI
Exercises, slides, and demos
How to download and complete exercises FREE
- Exercises download
- Demos download
- Slides of the video course
- SQL Server Contoso DW database
- How to download and complete exercises
Introduction to data modeling
Introduction to data modeling FREE
Analytical limits FREE
Increasing the analytical power FREE
Introducing the data model FREE
Leveraging the data model FREE
- Normalization and denormalization
- Facts and dimensions
- Introducing star schemas
- If you don't have a star schema
- Chains of relationships
- How many dimensions?
- Why data modeling is useful
- LAB number 1
- Introduction to data modeling
Header / detail tables
Header / detail tables FREE
- Introducing header / detail schemas
- Bidirectional filtering is not the way to go
- Header / detail
- Denormalizing the discount
- Back to a star schema
- LAB number 2
- Header / detail tables
Multiple fact tables
Multiple fact tables FREE
- Using multiple fact tables
- Moving filters with DAX
- Building a star schema
- How to properly use multiple fact tables, if present
- Trying bidirectional filtering
- Model ambiguity
- Solving ambiguity
- LAB number 3
- Multiple fact tables
Working with date and time
Working with date and time FREE
Date attributes in the fact table FREE
- Building a date dimension
- The model with a date dimension
- Automatic date grouping in Excel and Power BI
- Automatic date grouping in Power BI
- Quick calculations in Power BI Desktop
- Disable automatic date columns
Handling multiple dates FREE
Multiple date tables FREE
Multiple date tables with multiple fact tables FREE
- Multiple relationships with date
- Handling date and time
- Computing with working days
- Create a holidays table (one country)
- Create a holidays table (multiple countries)
- Weekends are not always the same
- Handling special periods of the year
- Non-overlapping periods: the model
- Non-overlapping special periods
- Overlapping special periods
- Overlapping period measure
- LAB number 4
- Working with date and time
Tracking historical attributes
Tracking historical attributes FREE
- Attributes change over time
- Handling variations over time
- Slowly changing attributes or dimensions?
- Rapidly changing dimensions
- Attributes in the fact table
- Tracking historical attributes
Using snapshots FREE
- What is a snapshot?
- Sales versus inventory in the same model
- Non-additive measures
- LASTDATE does not work here
- Optimizing performance
- Snapshots and granularity
- Transition matrix
- Parameter table
- LAB number 5
- Using snapshots
Analyzing date and time intervals
Analyzing date and time intervals FREE
- What are intervals?
- Solving with DAX... too complex!
- Changing granularity
- Split hours AND amount!
- Analyzing active events
- Open orders: the starting model
- Open orders with DAX
- Changing the model
- Open orders is a snapshot table
- Events with different durations
- Daily Salary (DAX)
- Precompute the values
- LAB number 6
- Analyzing date and time intervals
Many-to-many relationships FREE
- What are many-to-many relationships?
- Possible solutions to the scenario
- Bidirectional filtering
- Using CROSSFILTER
- Using expanded table filtering
- CROSSFILTER versus expanded tables
- Understanding non-additivity
- Cascading many-to-many
- LAB number 7
- Many-to-many relationships
Working with different granularities
Working with different granularities FREE
- Dimensions define granularity
- Analyzing budget data
- Reduce granularity on all the tables
- Using DAX to move the filters
- Filtering through relationships
- Use the correct column to slice
- Leveraging relationships
- Checking granularity in the report
- Hiding or reallocating?
- LAB number 8
- Working with different granularities
Segmentation data models
Segmentation data models FREE
Segmentation models FREE
Static segmentation FREE
Static segmentation: the formula FREE
- Dynamic segmentation
- Dynamic segmentation: the formula
- ABC and Pareto analysis
- Segmentation data models
Working with multiple currencies
Working with multiple currencies FREE
- Using multiple currencies
- Beware of simple calculations
- Multiple sources, one reporting currency
- Conversion with a calculated column
- Single source, multiple reporting currencies
- What the formula should perform
- Multiple sources, multiple reporting currencies
- Working with multiple currencies
- Enrico Vezzalini (Aug 20, 2018)
congratulazioni, il corso è molto ben fatto ed efficace! Se posso, vorrei aggiungere 2 suggerimenti: - sarebbe utile pensare ad un nuovo modulo orientato alla gestione e controllo dei modelli e del flusso dei dati in un'organizzazione complessa in relazione ai vari modelli di deployment - sarebbe molto interessante apprendere quali soluzioni si possano sviluppare mediante il data modeling per facilitare l'applicazione di tutti i requisiti di privacy by design e di compliance control nella creazione di una piattaforma di BI aziendale (sempre in relazione ai modelli di deployment di cui sopra ed all'utilizzo o meno dei filtri di confidenzialità di Power BI)
- Maria Luz Munoz (Aug 8, 2018)
It gave me the confirmation of thoughts and also gave me new ideas. I thank you for publishing this good course.
- Bill Brown (Jul 27, 2018)
Now have a much better understanding of data modeling.
- Emmanuel Dubosson (Jul 13, 2018)
after using Power Pivot for some years, I could with this course improve my data modeling skills to the next level. The core principles explained in the sections are good understable. Some topics have some (DAX) magic in it. I appreciated the ways proposed in many examples to simplify the data model. Doing it right, it's much more easier and performant. Thanks a lot! With this video course, I'm just only missing eating a pizza with Alberto or Marco.
- – Thanks!!
Reply by SQLBI (Jul 13, 2018)
- – Thanks!!
- Eduardo Rocha Clemente (Jun 24, 2018)
The last Module that I really have done the exercises was the "Analyzing date and time intervals". I think that the previous course that you advised me to do "Introducing Dax", the free one, was not enough to understand the solution that was depeloped in DAX code. I intend to do the "Mastering Dax" course, and do all the exercises again in this course to a better understanding . I feel that a roadmap to master DAX is needed
- – Thanks for the feedback!
Please, keep in mind that the goal of the Data Modeling for Power BI course is to teach how to set the goal in designing the data model, not in implementing the transformation. The way you have to consider the exercise is in practicing the definition of the data model. It would be better to use SQL or Power Query (M) to obtain such a result. For practical reasons, we used DAX to accelerate the creation of the required table, otherwise the course would have dedicated 70% of the time describing how to use SQL and/or Power Query, with a more complex setup for the exercises required.
Reply by SQLBI (Jun 24, 2018)
- – Thanks for the feedback! Please, keep in mind that the goal of the Data Modeling for Power BI course is to teach how to set the goal in designing the data model, not in implementing the transformation. The way you have to consider the exercise is in practicing the definition of the data model. It would be better to use SQL or Power Query (M) to obtain such a result. For practical reasons, we used DAX to accelerate the creation of the required table, otherwise the course would have dedicated 70% of the time describing how to use SQL and/or Power Query, with a more complex setup for the exercises required.
- Hana Palkova (May 10, 2018)
Many interesting new insights. Thanks Marco & Alberto!
- Paulo Rocha (May 7, 2018)
Wonderful! SQLBI, Marco and Alberto not only are the best in the field, bust also know how to share their knowledge. This approach of focusing in the Data Modeling and making more efficient DAX expressions takes us to a whole new level in Business Intelligence and Big Data. I'm very pleased with the content and the professional way everything was presented. Keep up the excellent work.
Do you prefer a course in classroom?This video course is based on a live, classroom course we teach all around the world. If you prefer a live learning experience, take a look at the dates below for a list of our upcoming events!
|Chicago, IL, US||Mar 25-27, 2019 Chicago|
|Amsterdam, NL||May 8-10, 2019 Amsterdam|