A data warehouse can store historical data, allowing analysts to evaluate multiple sources of data in order to gain actionable insights. A data warehouse can either be deployed on-premises or in the cloud. The choice you make depends on your business’s requirements and other factors like cost and scalability, security, control, and resources.
Data warehouses are built to store large amounts historical enterprise data as well as performing in-depth analysis of data for business intelligence and reporting (BI). They can hold relational or nonrelational information. They are typically structured, which means that the data is loaded and extracted after which it is transformed to schemas that are pre-defined prior to being stored. This makes it easier to run queries against them instead of directly against the operational source system.
Traditional data warehouses on premises need expensive equipment and software to host them. They have limited storage compared to the computing power, and they must regularly discard older data to make room for newer data. A data warehouse enables you to run historical inquiries that are not possible in operational systems, since they only refresh with real-time data.
A cloud-based data warehouse, or managed service, is an automated and highly efficient solution that’s a good option for businesses that need to analyze huge quantities of data over time. It is often a more cost-effective alternative to traditional data warehouses as it eliminates the need to install large servers and also offers a flexible pricing. You can pay by the hour or throughput, or a fixed amount of resources.
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