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A data warehouse is an archive of historical data that enables analysts to analyze data from different sources to gain actionable insights. Data warehouses can be deployed on-premises or in the cloud. The choice you make will depend on your needs as a business and other considerations such as scalability, cost, resources, control and security.
Data warehouses are created to store large amounts historical data from enterprises and for carrying out deep 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 the data is loaded and extracted and then transformed according to predefined schemas prior to being stored. This makes it easier to run queries against them than directly against an operational source system.
Traditional on-premises data warehouses require expensive hardware and software in order to host them. They are limited in storage to the compute power and must continually discard older data to make way for the newest data. A data warehouse enables you to conduct historical searches that are impossible using operational systems, as they only refresh using real-time data.
A cloud-based storage, or managed service is a fully automatic and highly efficient solution. It is perfect for companies that need to analyze large amounts of data in the long run. It is often a superior alternative to data warehouses that are on-premises because it eliminates the need for huge servers, and offers flexible pricing with pay per throughput or per hour of usage, or with a fixed price for a set amount of resources.