A data warehouse is a collection of historical information that allows analysts to analyze data from various sources to extract actionable insights. A data warehouse can either be installed on premises or in the cloud. The decision you make will depend on your specific business requirements and other factors like cost and scalability, security, control and resources.
Data warehouses are created to store large amounts historical data from enterprises and for carrying out deep analysis of data for business intelligence and reporting (BI). They can store both non-relational and relational data. They are typically structured, meaning that the data is extracted, loaded and transformed (ELT) to be in line with pre-defined schemas prior to when it’s stored. This allows you to run queries against them much easier than executing them directly against operational source systems.
The traditional on-premises warehouses require expensive equipment and software to be hosted. They are limited in storage to the compute power, and they must regularly discard old data to make space for more recent data. A data warehouse allows users to run historical queries that are impossible on operational systems because they only update with real-time data.
A cloud-based, data store or managed service, is an entirely automated and highly performant solution. It is ideal for businesses virtual data warehouses that need to analyze large amounts of data over the long-term. It is usually a better alternative to data warehouses that are on-premises since it does not call for huge servers, and also provides flexible pricing, with pay per throughput or per hour of usage or with a fixed cost for a predetermined amount of resources.