A data warehouse stores historical data, allowing analysts to analyze multiple sources of data in order to discover dataroomtechs.info/what-does-a-venture-capitalist-look-for-in-a-start-up actionable insights. A data warehouse can either be deployed on-premises or in the cloud. Which option you choose is contingent on your business requirements and other factors like scalability cost resources, control and security.

Data warehouses are designed for storing large amounts of historical enterprise data, as well as for performing in-depth data analysis for business intelligence and reporting (BI). They can be used to store both non-relational as well as relational data. They are typically structured, meaning that data is extracted, loaded and transformed (ELT) to conform to pre-defined schemas before it’s stored. This makes running queries against them a lot simpler than directly against operational source systems.

Traditional data warehouses on premises require expensive hardware and software to host them. Their storage capacity is limited to their compute and they must constantly discard older data in order to keep enough space for the latest data. A data warehouse permits you to run queries on historical data that aren’t possible using operational systems, as they only refresh using real-time data.

A cloud-based storage, or managed service is fully automated and a highly efficient solution. It is ideal for organizations who need to analyze large amounts of data in the long-term. It is often a better alternative to data warehouses that are on-premises because it eliminates the need for oversized servers, and also offers a flexible pricing structure with the option of paying per hour of use or with a fixed cost for a predetermined amount of resources.