Data Engineer Data Pipeline Design Interview Questions

Kshitij I. - "Data lake and warehouse are both places that allow an organization to store large amounts of data. When swimming in a lake, one would imagine that they come across all sorts of stuff - floating twigs, fish in the water, stones, chemicals and sometimes may be even a snake. Similarly, a data lake stores all forms of data that the company has without any indexing. The data is available at any time but needs to be first cleaned up and reorganized before it can be used for any type of analysis. A"See full answer

Joshua R. - "Hadoop is better than PySpark when you are dealing with extremely large scale, batch oriented, non-iterative workloads where in-memory computing isn't feasible/ necessary, like log storage or ETL workflows that don't require high response times. It's also better in situations where the Hadoop ecosystem is already deeply embedded and where there is a need for resource conscious, fault tolerant computation without the overhead of Spark's memory constraints. In these such scenarios, Hadoop's disk-b"See full answer