By IT Brew Staff
less than 3 min read
Definition:
Data warehouses often consolidate a variety of data from across an organization, including customer relationship management (CRM) and enterprise resource planning (ERP) platforms, and are intended for reporting and trend analysis, as well as business intelligence (BI) uses. As a result, they are best suited for data that needs to be analyzed quickly as opposed to massive amounts of unstructured data (a data lake is better for the latter).
A typical data warehouse configuration involves tiers. The bottom tier is where data is collected from multiple systems and stored; this often involves an extract, transform, load (ETL) process to clean and structure data. The middle tier is an analytics engine that can access and analyze the data from the bottom tier. The top tier is the user interface, and presents stakeholders with dashboards and tools for generating reports.
For many years, data warehouses were hosted on-premises via hardware maintained by an organization. With the advent of the cloud, however, many organizations opted to host their data warehouses with third-party cloud vendors, which can remove many of the infrastructure costs associated with on-premises hosting (and allow teams to focus on the benefits of the warehouse—such as data analytics—without worrying about maintenance). Some organizations may choose a hybridized approach to warehousing, storing their most sensitive data in an on-premises setup while sending the rest to the cloud for storage and analysis.
