On-premises and cloud data lakes are popular for enabling analytics, big data storage, self-service data practices, and warehouse modernization. However, data management challenges can often make finding value extremely difficult. In fact, when data lakes first entered the market, many organizations simply dumped data into the lake, transforming them into entities more akin to swamps that were nearly impossible to leverage, navigate, or trust. The uncontrolled and undocumented swamp was the first generation of a data lake that had many failings, but it also provided numerous learning opportunities. Second generation data lakes have better internal organization, are typically governed better, and make use of modern ingestion technologies that support all forms of data and metadata integration. In addition, they leverage automated data pipelines as a best practice. . You will learn: - The evolution and necessity of the modern data lake - Options for efficient, real-time data ingestion at scale - The importance of data pipeline automation.