Lakehouses promise to deliver on all the benefits of data lakes and data warehouses, combined. The idea is that unstructured and structured data can live in one repository, equally supporting both data scientists and BI and analytics users, while lowering costs and also improving processing power and flexibility.
As much as the blend benefits, however, data lakehouses also combine the weaknesses of data warehouses and data lakes, and a logical data fabric is still a necessity to unlock the full value from these new cloud offerings. If big data is any indication, most large organizations never put all of their data into a single repository because of both the effort and cost involved.
In this session, Ravi will discuss the hype and reality of data lakehouses. He will describe how a data lakehouse figures into a logical data fabric. He will explain how a logical data fabric offsets the weaknesses of lakehouses, and he will go in-depth on data virtualization as an architectural core component of logical data fabrics.