Many companies have invested heavily in building data lakes to store large volumes of structured and unstructured data from various sources into Delta Parquet files. These Delta Parquet files can be used for a wide range of Analytics and Business Intelligence applications. Most of these organizations struggle to derive insights from their investments due to the complexity of accessing and querying the data, and how to let self-service users connect to this data in the lake using Power BI.

With the introduction of Microsoft Fabric, an all-in-one analytics solution for enterprises, we now have a better approach for this. In this session, we will explore how to use Lakehouse data at scale with Power BI, using the new Direct Lake connectivity mode. Power BI Direct Lake combines the best of both worlds from Import and DirectQuery mode, and gives us the option for great performance over data in the lake, without introducing additional latency for dataset refreshes.

We will start by discussing the benefits of the Lakehouse architecture and how it can improve data management and analytics. We will then move on to explore how to connect to Lakehouse data using Power BI by combining both of these architecture components and using each of them to their strengths.

We will also cover best practices for optimizing performance when working with large volumes of data, including using data partitioning and query optimization techniques. We will demonstrate how to use Power BI to analyze Lakehouse data in real-time and how to build reports that provide actionable insights for decision-making.

By the end of the session, attendees will have a solid understanding of how to leverage Lakehouse data at scale with Power BI and how to build powerful analytics solutions that can handle massive amounts of data. Whether you are a data analyst, data scientist, or BI professional, this session will provide you with valuable insights into the world of Lakehouse data and Power BI, featuring the new Direct Lake connectivity mode.