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  This post reviews some of the tips and techniques that I covered in my webinar   Performance Techniques for Power BI Data Models . To save blog space I have highlighted the first 5 tips from the presentation. There are more tips and techniques, along with expanded explanations and references in the   presentation slides . The Problem Power BI  is  fast, and the columnar data store is forgiving of large data sets. However, if you find that your Power BI desktop solution is slowing down or that the refresh of a published BI data set takes a very long time review these tips to see if they can help you streamline your data model and reports. My example data for this talk is a customized Tasks table from Salesforce. This real life data table comes from a client and is sanitized for confidentiality. The example has over 382,000 rows which isn’t a large table for Power BI. When the data is loaded into Power BI, the stored file size on disk balloons to over 500MB. In memory this data set occ

  When you create a data model in Power BI, you should consider how to properly use naming convention and what columns to include, in order to improve usability and performance. This article provides a quick list of best practices valid for both Power BI and Power Pivot. APR 5, 2018 UPDATED Marco Russo DAX     POWER BI     POWER PIVOT     TABULAR    Not all of the suggestions described can be applied to all of your data models. You should adapt these best practices to your specific scenario, looking at how to achieve the goals that are the reason for a certain pattern more than barely apply it without considering the pros and cons of each choice. Even if the article mentions Power BI, all the best practices described are valid for Power Pivot and Analysis Services Tabular models, too. The demo file you can download (at the end of the article) contains a sample Power BI file and the corresponding views defined in a SQL file for AdventureWorksDW. Use views Always import views and never i