A data warehouse is loaded with data from numerous heterogeneous sources into a central repository for analytics. Data warehouses store multidimensional information in a way that allows analytics to be efficiently performed. Data warehousing helps organizations in effective decision-making, and is at the heart of business intelligence.

Unlike operational databases where data is frequently updated as transactions occur, updates are scheduled at intervals in a data warehouse. Additionally, data warehousing provides an organization access to current and historical data to analyze its performance to strategically plan its future.

Data warehousing supports Online Analytical Processing tools, which help in multi-dimensional data analysis. In data warehousing, data mining works together with OLAP operations to boost knowledge mining at multiple levels of abstractions.

Data warehousing uses three techniques to analyze data: Data Mining, Analytical Processing, and Information Processing. The functions of the data warehousing utilities are data extraction, data cleansing, data transformation, data loading, and refreshing.

Advantages of Data Warehousing

Data warehousing…

  • Provides higher data consistency.
  • Provides enhanced query performance.
  • Cleans the data using data cleansing.

Applications of Data Warehousing

Data warehousing is used in many businesses to easily combine data from multiple sources. For example, a business may combine customer information from its website, sales history from cash registers, and information from comment cards into one data warehouse. From there, data mining can be used to look for patterns that will help the company make informed business decisions.

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