Data warehousing is the process of collecting, organizing, and managing data from various sources into one comprehensive database to provide meaningful business insights and forecasts to respective users. It 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 warehouse is developed by integrating data from varied sources into a consistent format. The data must be stored in the warehouse in a consistent and universally acceptable manner in terms of naming, format, and coding. This facilitates effective data analysis. Non-Volatile Data once entered into a data warehouse must remain unchanged. All data is read-only. Previous data is not erased when current data is entered. This helps you to analyze what has happened and when. Time-Variant.

Examples of data warehousing in various industries include:

• Amazon - Amazon Redshift
• Google - Google BigQuery
• IBM - IBM Db2 Warehouse
• Marketing campaigns and strategies
• Customer behavior
• Market statistics
• Positioning in networks and search engines
• Productivity indexes
• Social

Data warehousing provides several benefits to end-users, including improved access to a wide variety of enterprise data, increased data consistency, additional documentation of the data, potentially lower computing costs and increased productivity, and providing a single source of truth for the organization.