A Data Lake is a repository of data stored in its natural state, and is composed of five key components: ingestion, storage, cataloguing, processing, and governance. Ingestion is the process of collecting data from various sensors, sources and systems; Storage ensures that data remains securely stored for access whenever needed; Cataloguing assigns metadata to the ingested data so it can be easily indexed and located; Processing includes analyzing or transforming the data into meaningful insights; Governance enforces rules and compliance on the data lake’s usage. With the right combination of these components, organizations are able to make optimal use of data-driven decisions and gain business insights.