Data lakes are often pitched as the solution to many traditional data management solutions' woes, but in reality, they can lead to various challenges such as high costs, difficult management, long time-to-value, immature governance and security, problematic data skills, and exponential data growth. To overcome these issues, organizations need to rethink their data lake architecture and management, leveraging cloud resources, removing data silos, and investing in building a culture of data literacy. Additionally, embracing self-service analytics, modular security data lakes, and open-source components can help reduce costs and improve efficiency.