A data warehouse is a system that aggregates data from different sources into a single, central, consistent data store to support data analysis, data mining, artificial intelligence (AI), and machine learning.
What Is a Data Warehouse?
A data warehouse system enables an organization to run powerful analytics on huge volumes (petabytes and petabytes) of historical data in ways that a standard database cannot. Traditionally, a data warehouse was hosted on-premises—often on a mainframe computer—and its functionality was focused on extracting data from other sources, cleansing and preparing the data, and loading and maintaining the data in a relational database. More recently, a data warehouse might be hosted on a dedicated appliance or in the cloud, and most data warehouses have added analytics capabilities and data visualization and presentation tools.
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Data Warehouse Architecture
Generally speaking, data warehouses have a three-tier architecture, which consists of |
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- Top tier: It is represented by some kind of front-end user interface or reporting tool, which enables end users to conduct ad-hoc data analysis on their business data.
- Middle tier: It consists of an OLAP (i.e., online analytical processing) server which enables fast query speeds.
- Bottom tier: It consists of a data warehouse server, usually a relational database system, which collects, cleanses, and transforms data from multiple data sources through a process known as Extract, Transform, and Load (ETL) or Extract, Load, and Transform (ELT).
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