Examining data lake essentials for data engineers
Large volumes of unprocessed data can now be cost-effectively and flexibly stored with data lakes. We’ll examine the layers and architecture of data lakes in this section, explaining their differences from data warehouses and situations in which using one is preferable. We’ll explore the key areas of a data lake, discussing their special features and the kinds of situations in which a data engineer could interact with them.
Data lake architecture
A data lake’s architecture encompasses more than just the zones that make up the lake. It is a combination of different parts that make data intake, storage, processing, and consumption easier. Gaining an understanding of the architecture will enable you to create and run a data lake efficiently as a data engineer. Let’s examine the essential components of a data lake architecture in more detail:
