A data warehouse is a relational or multidimensional database that is designed for query and analysis. They are not optimized for transaction processing, which is the domain of OLTP systems. Data warehouses usually consolidate historical and transactional data derived from multiple sources. Data warehouses separate analysis workload from transaction workload and enable an organization to consolidate data from several sources.
Data in a data warehouse usually stores many months or years of data to support historical analysis. The data in a data warehouse is typically loaded through an extraction, transformation, and loading (ETL) process from one or more data sources such as OLTP applications, mainframe applications, or external data providers.
End users of the data warehouse perform data analyses that are often time-related. Examples include consolidation of last year's sales figures, inventory analysis, and profit by product and by customer. More sophisticated analyses include trend analyses and data mining, which use existing data to forecast trends or predict futures. The data warehouse typically provides the foundation for a business intelligence environment.
Data in a data warehouse usually stores many months or years of data to support historical analysis. The data in a data warehouse is typically loaded through an extraction, transformation, and loading (ETL) process from one or more data sources such as OLTP applications, mainframe applications, or external data providers.
End users of the data warehouse perform data analyses that are often time-related. Examples include consolidation of last year's sales figures, inventory analysis, and profit by product and by customer. More sophisticated analyses include trend analyses and data mining, which use existing data to forecast trends or predict futures. The data warehouse typically provides the foundation for a business intelligence environment.
