Data Lake And Data Warehouse: Collision or Synergies? Featuring Pharmeasy & Swiggy
The data that organizations collect and process must be stored in a way that allows them to leverage it: to report on the past, to understand the present, and to predict the future. Data warehouses support reporting and analytics on historical data while data lakes support newer use cases that leverage data for machine learning, predictions, and real-time analysis. The question is: do you need both and why? Listen to how Dhaval Bonde, Team Lead at Swiggy, and Abhijit Singh at Pharmesy approach data lakes and data warehouses.