The progression from data warehouses to big data to data lakes and now to data lakehouses is probably not over. The data warehouse is built to report on business operations with some analysis for predictive modeling (forecasting) or discovery. A limited group of experts has access. Big data was typically housed in a file-based or object-based repository where it waited, uncategorized and raw, for intrepid analysts to mine it for insights. The data lake architecture evolved from the big data repository. Then came the data lakehouse.
Tomer Shiran, Co-founder and CPO of Dremio, titled his keynote at Subsurface 2023 “The Year of the Data Lakehouse.” Tomer took the time to sit down with Cloud Data Insights (CDI) and explain why that’s so. He covered related topics like the importance of the semantic layer, performance optimization, and emerging capabilities in data lakehouses.
Read the full interview here.
