Microsoft Fabric has incorporated a number of different elements into one environment for data lakes with OneLake, data warehousing, machine learning, data transformation, and reporting. In this session we will look at using OneLake for data lakehouses and demonstrating how OneLake can be used instead of a database highlighting the performance improvements which have been made. Demonstrations will show the ability to use Fabric to connect to data from different sources and from different data lakes to ensure compliance with GDPR or other location-based regulations with OneLake. We will examine what a Fabric data lakehouse entails and how the data is integrated into Power BI for reporting. Changes in Spark clusters and Delta file implementation are examined to ensure you will understand how these improvements will impact your data movement pipelines and machine learning tasks. Data science workflows are reviewed to provide a good explanation of not only how to use them, but also the best practices for integrating these objects into pipelines. We will investigate how using the new Dataflow2 data transformations can speed up development and when they would be a good implementation choice. We will also examine the different ways Copilot is incorporated within Fabric so that your organization can be on the cutting edge of AI development with ChatGPT technology. This session will show you how to leverage Fabric’s different components for data driven decision making within your organization.