Data in the modern enterprise is highly distributed, diverse, and dynamic. Organizations are evaluating and implementing multiple architectural approaches to activate data for enterprise intelligence. Some are using cloud data warehouses, data lakes, lake houses, fabrics, meshes, and data control planes. Regardless of what architectural approach is used, the foundational element that needs to exist is data intelligence, fueled by metadata. Data intelligence should be the first thing that organizations harvest and curate before deciding where data needs to be, and how it can be utilized in enterprise intelligence use cases.