Integrating BI and data visualization tools with a data lake is becoming increasingly important as enterprises struggle to cope with the growing complexity, scale, and speed of their data. Traditionally, business intelligence (BI) and data visualization tools relied on structured data from data warehouses or data marts, but modern data lakes are changing this paradigm by providing a centralized repository for enterprise data in its raw format. However, integrating BI and data visualization tools with a data lake poses several challenges, including non-relational data structures, swampy data lakes, and poor query performance. To overcome these challenges, organizations can adopt strategies such as passing data through their data warehouse, choosing a BI platform with data lake connectors, or adopting a cloud data platform with built-in BI capabilities. By integrating BI and data visualization tools with a data lake, enterprises can unlock new insights and make data-driven decisions more efficiently.