Data Modeling for Power BI Video Course
Data modeling is a required skill to get the most 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 video 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 video course is made up of over 10 hours of lectures, plus another estimated 8 hours of individual exercises. You can watch the videos at any time and the system will keep track of your progress. Within the video 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.
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- Douglas Chapman (May 29, 2020)
Excellent course. The DAX syntax was a little over my head, but the modelling components really taught me a great deal of how to properly structure project models. My key take away... don't use explicit tables values and always question your data to see if it "really" meets your requirements. There are tons of gotchas explained in this course. Highly recommended.
- Sue Bayes (May 15, 2020)
I really enjoyed this course and understanding the most efficient way to build a model to create business calculations. Particularly enjoyed not only the exercises at the end of each section, but the ability to work through the demonstration examples and then apply to my own models.
- Ferdinand Santos (Apr 19, 2020)
Comments: 1. Safari browser on an iPad doesn't automatically play the next video. Edge browser on a PC does. 2. In the interface, please provide a way to bookmark points in the videos and the ability to go back to them later by picking from a list of bookmarked timestamps.
- – Thanks for the feedback - we are not sure how much we can customize the player, we are investigating in possible improvements!
Reply by SQLBI (Apr 21, 2020)
- – Thanks for the feedback - we are not sure how much we can customize the player, we are investigating in possible improvements!
- Tomasz Halas (Apr 15, 2020)
Great Course !
- Melissa Valgardson (Mar 7, 2020)
Excellent course. Now I have many ideas on how to improve the data models I've been working with!
- Amaru Quinones (Mar 5, 2020)
Simply Awesome! Structured, organised, user friendly, and with good practice step by step. I enjoyed it and learnt a lot, as it is also, super clear to follow and understand.
- Gail Kulak (Feb 24, 2020)
Great course with only one comment - too bad the last two sections don't have any labs. Luckily I have the book and did the exercises associated with the book. How about incorporating them here?
- Robert Williams (Jan 20, 2020)
The course subject and topics covered is really interesting and great explanation. However, it is really frustrating so far as you cannot complete this course unless you know DAX, and I'm not talking about the free dax course, it needs to go higher because it is assumed you understand how dax and each of it's functions work in order to complete each of the tasks/challenges at the end of each module. That was never made clear when buying the course! It should be clearly stated that you should either complete one of the more advanced DAX courses first, or take a quick self test on DAX questions to ensure your level is high enough before buying this course.
- – Hi Robert, we're sorry you feel this way. The purpose of the course is to show what is the right way to create a data model in order to simplify the DAX code required. Most of the DAX code shown in the course is actually what is required in case you do not have a proper data model.
Once this first goal is achieved (understanding what is the right data model), then you have to transform the source data in case it doesn't fit the model. There are many tools you can use for that: SQL queries, ETL tools, Power Query (with M language). Sometimes you can use DAX, even though this is not necessarily the best tool for the job, maybe with the exception of some data model based on snapshot tables. Our experience is that knowing the right data model is a very useful skill for Power BI users, even though they don't know data tools and languages and don't want to / cannot spend time to learn them, because they can ask for the data in a proper format from someone else, maybe a co-worker in the company for example.
If you want to achieve proficiency in data transformation, you need to use Power Query/M or SQL or other commercial ETL Tools (Informatica, Integration Services, Azure Data Factory, and many others). However, knowing these tools without having a goal (like the star schema we discuss in the course) could lead to models that solve the problem for a specific report and not for a generic semantic model, as a Power BI model can be.
We made the choice to show some transformation in DAX because it was the easiest to use and deploy for the examples. The alternative would have required a more complex setup for the data sources, with the risk of losing time with configuration details while the focus should be on the concepts contained in the course.
Please, contact us at info (at) sqlbi (dot) com if you want to provide additional feedback about the tools you would have liked to see to perform data transformation. We are always looking for feedback that can help us improve the content.
We also hope that this explanation will help other readers that evaluate this course.
Thanks!
Reply by SQLBI (Jan 20, 2020)
- – Hi Robert, we're sorry you feel this way. The purpose of the course is to show what is the right way to create a data model in order to simplify the DAX code required. Most of the DAX code shown in the course is actually what is required in case you do not have a proper data model.
Once this first goal is achieved (understanding what is the right data model), then you have to transform the source data in case it doesn't fit the model. There are many tools you can use for that: SQL queries, ETL tools, Power Query (with M language). Sometimes you can use DAX, even though this is not necessarily the best tool for the job, maybe with the exception of some data model based on snapshot tables. Our experience is that knowing the right data model is a very useful skill for Power BI users, even though they don't know data tools and languages and don't want to / cannot spend time to learn them, because they can ask for the data in a proper format from someone else, maybe a co-worker in the company for example.
If you want to achieve proficiency in data transformation, you need to use Power Query/M or SQL or other commercial ETL Tools (Informatica, Integration Services, Azure Data Factory, and many others). However, knowing these tools without having a goal (like the star schema we discuss in the course) could lead to models that solve the problem for a specific report and not for a generic semantic model, as a Power BI model can be.
We made the choice to show some transformation in DAX because it was the easiest to use and deploy for the examples. The alternative would have required a more complex setup for the data sources, with the risk of losing time with configuration details while the focus should be on the concepts contained in the course.
Please, contact us at info (at) sqlbi (dot) com if you want to provide additional feedback about the tools you would have liked to see to perform data transformation. We are always looking for feedback that can help us improve the content.
We also hope that this explanation will help other readers that evaluate this course.
Thanks!
- Rega Sanyoto (Jan 5, 2020)
Great content from basic to advanced concept of data modelling using DAX. Highly recommended for every BI professionals
- MICHEL PLATINI DE ALMEIDA CESAR (Dec 13, 2019)
Perfect methodology and didactics! For sure the best course in the market!
- Ivon Ampuero (Dec 4, 2019)
Great course
- Richard Valdez (Nov 18, 2019)
This is a fantastic course!! I am studying this course concurrently with the Mastering DAX course and I am finding it quite useful to go back between both courses. I am eager to continue in this wonderful journey of learning the DAX language and applying it to my work.
- Robin Neven (Oct 25, 2019)
Very good: clear explanations and examples, though harder than I had expected. But that's good because it means there was a lot to learn! Minor point of improvement: sometimes the assignments weren't totally clear to me. In those cases it started with a description, but never really asked a question/gave an assignment.
- Lucas Minikoski (Oct 24, 2019)
Thank's, this course leveled me to another way of "DAXing". Now I feel better when I open the PBI and start measuring. Thank's a lot!!!!
- Abhijith DSouza (Oct 16, 2019)
Thank you Marco and Alberto for a wonderful course. A lot of real world applications were covered in the course and also different techniques to solve them. I particularly enjoyed the techniques which we shouldn't use and the reasons for not using them. Highly recommended for anyone interested in an in depth analysis for Power BI data modeling.
Would you prefer a classroom course?
This video course is based on a classroom course we teach all around the world. If you prefer a classroom learning experience, take a look at the dates below for a list of our upcoming classroom courses!Amsterdam, NL | Dec 10-12, 2024 Amsterdam |