For the past two years, my team has been working on a premium Power BI model that has grown significantly in size, from 50 GB to over 100 GB. During this time, we have gained valuable insights and lessons that we would like to share with you. These include the importance of conducting systematic testing, determining which features and columns will have the most impact on performance, and managing the ongoing refresh of a model of this size. We hope that these tips will be helpful for those looking to optimize and improve their Power BI models.

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Alex Dupler is a Power BI developer and architect at Microsoft, where he currently serves as the lead Program Manager for a data warehouse platform supporting the company's advertising business. In this role, Alex is responsible for a Power BI import dataset with 90 GB of data. He is also one half of "Two Alex's," a YouTube channel that features live discussions on Power BI topics without one correct answer. Prior to joining Microsoft, Alex worked as a chemist. He is a member of the PBICAT team and has been inactive for a while.

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