Data lakes

Data lakes have become an increasingly popular way for organizations to store and manage large amounts of structured, semi-structured, and unstructured data. In this overview, we’ll dive deep into the technical aspects of data lakes, including their architecture, data ingestion and processing, storage and retrieval, and security considerations.

Architecture

At its core, a data lake is an architectural approach to storing data that allows for the aggregation of large volumes of disparate datasets in their original formats. This means that data can be ingested from a wide range of sources, including databases, data warehouses, streaming data sources, and even unstructured data such as social media posts or log files. The data is typically stored in a centralized repository that spans multiple servers or nodes and is accessed using a distributed filesystem such as Hadoop Distributed File System (HDFS), Amazon Simple Storage Service (Amazon S3), or Microsoft Azure...