Typically, a data warehouse is a larger data repository designed to store all types of business information in a central location. It also supports data analysis, artificial intelligence, and machine learning.
Historically, most data warehouses were hosted on-premises. However, many today are cloud-based. This can give them a number of benefits, such as improved governance, security, data sovereignty and better latency.
Better, faster analysis - A data warehouse aggregates, unifies and harmonizes data from multiple sources to create a complete picture of a company's history. This provides the foundation for advanced BI activities, such as data mining and augmented analytics, to uncover patterns and trends that would be easily missed if they were dispersed among individual data silos.
A warehouse combines operational data (current transactions) with time-variant information about the business. This allows companies to track past performance and prepare for future growth.
Consistent data - The information in a warehouse is clean, consistent and de-duplicated. This improves data quality and reduces the risk of misunderstanding or inconsistencies between reports generated from different source systems.
Data warehouses use a process called extract, transform and load or ETL to move data from source systems into the warehouse. This transforms the data to be consistent with the warehouse's data model, which defines the format and structure of all the data within the system.
A warehouse enables organizations to organize their data so it makes sense to people. This is a significant advantage for businesses that operate in real-time and need to react quickly to changing conditions. It enables them to make sound decisions based on facts, rather than guesswork.