Congratulations! You’ve built your beautiful Power BI report and your charts look terrific, but your data refresh takes forever or, your report renders slow when interacting with visuals. In this course, Optimize Model Performance with Power BI, you’ll gain the ability to improve the efficiency of your Power BI reporting solution. First, you’ll explore how to reduce the data model size by removing unnecessary columns and rows. Next, you’ll discover the importance of the column cardinality and how it can affect data model performance. Then, you’ll also understand the benefits of using aggregations feature to make things running faster. Finally, you’ll learn how to identify and resolve poorly performing report elements, such as measures and visuals. When you’re finished with this course, you’ll have the foundational understanding of data model optimization techniques that will enable you to build more efficient Power BI solutions and get you ready for the PL-300 exam.
Author Name: Nikola Ilic
Author Description:
Nikola Ilic is an officially Business Intelligence Developer, focusing on Microsoft Data Platform technologies, especially Power BI – but “off the record” he is a data fanatic, interested in everything related to extracting meaningful information from the raw data. Nikola is self-proclaimed “Data-Mozart”. As he lives in the wonderful city of Salzburg, Austria, which is well-known as the birthplace of W.A.Mozart, he was brave enough to use the composer’s last name as part of his nickname. That’… more

Table of Contents

• Course Overview
  1min
• Understanding Core Concepts of Performance Optimization
  21mins
• Optimizing Data Model Performance by Improving Cardinality Levels
  18mins
• Optimizing Data Model Performance with Aggregations
  12mins
• Identifying Poorly Performing Report Elements
  11mins