Data lake vs. Data warehouse
What is the difference between a data lake and a data warehouse?A data lake and a data warehouse are two different approaches to managing and storing data. A data lake is an unstructured or semi-structured data repository that allows for the storage of vast amounts of raw data in its original format. Data lakes are designed to ingest and store all types of data — structured, semi-structured or unstructured — without any predefined schema. Data is often stored in its native format and is not cleansed, transformed or integrated, making it easier to store and access large amounts of data.A data warehouse, on the other hand, is a structured repository that stores data from various sources in a well-organized manner, with the aim of providing a single source of truth for business intelligence and analytics. Data is cleansed, transformed and integrated into a schema that is optimized for querying and analysis.Reference: https://www.databricks.com/glossary/data-warehouse
What is the difference between a data lake and a data warehouse?
A data lake and a data warehouse are two different approaches to managing and storing data.
A data lake is an unstructured or semi-structured data repository that allows for the storage of vast amounts of raw data in its original format. Data lakes are designed to ingest and store all types of data — structured, semi-structured or unstructured — without any predefined schema. Data is often stored in its native format and is not cleansed, transformed or integrated, making it easier to store and access large amounts of data.
A data warehouse, on the other hand, is a structured repository that stores data from various sources in a well-organized manner, with the aim of providing a single source of truth for business intelligence and analytics. Data is cleansed, transformed and integrated into a schema that is optimized for querying and analysis.