Fivetran has shifted its stance on data lakes due to changing customer needs, with large volumes of semi-structured and unstructured data becoming more common, making the cost advantages of data lakes more meaningful, particularly for AI and machine learning. Data lakes are increasingly capable in terms of cataloging, governance, and handling structured data, as well as security and regulatory compliance. The functions and capabilities of data warehouses and data lakes are consolidating under a common cloud data platform or data lakehouse, simplifying an organization's data architecture. Automated data movement unlocks the potential of the data lake by streamlining the data pipeline and reducing labor-intensive transformation stages, allowing for more efficient data engineering and data science efforts.