Data Ecosystems have emerged from the Cloud Service Providers (CSPs) and Independent Software Providers (ISVs) over the past few years. They offer an integrated set of tools for end-to-end data management for all data use cases, such as Analytics, ML, AI, Applications, Edge computing and more. Data Ecosystems will have a profound effect on data and analytics strategy, vendor and product choices and management of systems across clouds and hybrid.

Confusion persists regarding the role of data warehouses, data lakes and data hubs — no complicated further with the “lakehouse.” While the names and terminology are less important than the principles and capabilities, D&A leaders need to know the capabilities, use cases and the value they provide.
• What are different data repository models in use today?
• What are the key differences between these models?