A data warehouse can store historical data, allowing analysts to evaluate multiple sources of data to extract actionable insights. A data warehouse can either be deployed on-premises or in the cloud. The choice you make is contingent on your business’s requirements and other factors like scalability and cost, security, control, and dataroomtechs.info/what-does-a-venture-capitalist-look-for-in-a-start-up resources.
Data warehouses are made to store large amounts historical enterprise data as well as performing in-depth analysis of data for reporting and business intelligence (BI). They can store relational as well as non-relational data. They are typically structured, which means that the data is loaded and extracted, then transformed to conform to the predefined schemas before being stored. This makes it easier to run queries against them, rather than directly against an operational source system.
The traditional on-premises warehouses require expensive hardware and software in order to be hosted. They have a limited storage capacity when compared to compute power and must constantly delete older data in order to make room for newer data. A data warehouse allows you to run historic queries which are not possible on operational systems because they only update with real-time information.
A cloud-based data store, or managed service is an entirely automated and extremely efficient solution. It is perfect for companies that need to analyze large amounts of data in the long-term. It is often a more cost-effective alternative to traditional data warehouses, since it doesn’t require you to have large servers and also offers a flexible pricing. You can pay per the hour or throughput, or the amount of resources you are allocated.
