Data warehouses gather data from multiple sources into a central access point. That data is then transformed into structures specified in predefined schemas designed for data analytics. (More about these transformations is covered in “The architecture of a modern data warehouse,” below.)
Data warehouses gather data from multiple sources into a central access point. That data is then transformed into structures specified in predefined schemas designed for data analytics. (More about these transformations is covered in “The architecture of a modern data warehouse,” below.)
Data warehousing is the
process of constructing and using a data warehouse. A data warehouse is constructed by integrating data from multiple heterogeneous sources that support analytical reporting, structured and/or ad hoc queries, and decision making. Data warehousing involves data cleaning, data integration, and data consolidations.A data warehouse is a type of
data management system that facilitates and supports business intelligence (BI) activities, specifically analysis. Data warehouses are primarily designed to facilitate searches and analyses and usually contain large amounts of historical data.A Data Warehousing (DW) is
process for collecting and managing data from varied sources to provide meaningful business insights. A Data warehouse is typically used to connect and analyze business data from heterogeneous sources. The data warehouse is the core of the BI system which is built for data analysis and reporting.
A Data Warehouse can be viewed as a data system with the following attributes:
- It is a database designed for investigative tasks, using data from various applications.
- It supports a relatively small number of clients with relatively long interactions.
Key Takeaways
- A data warehouse is the storage of information over time by a business or other organization.
- New data is periodically added by people in various key departments such as marketing and sales.
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