Data warehouse
Data warehouse
Data warehouse definition
A data warehouse is a centralized repository for data collected from various different sources. The primary goal of data warehouses is to make sure that the data gathered across an organization has a common point of reference and can be used for comparison (and is thus useful for business analysis).
See also: sensitive information, extraction, data custodian, data mining, predictive data mining, machine learning
Real data warehouse uses
- Consolidating data from multiple systems (such as apps or databases) into a single location.
- Keeping large volumes of historical data to let organizations analyze trends and patterns over time.
- Letting users share customized reports based on the available data.
- Providing a platform for business analysis and comparison. The resulting insights help executives and departments make informed decisions.
- Providing an environment for AI training, including deep learning and machine learning.
How data warehouses operate (the ETL process)
- Extraction (E) is the collection of data from various sources for transformation. Extraction involves identifying the relevant data, filtering it, and preparing it for processing.
- Transformation (T) is the act of standardizing the extracted data into a common format. Transformation ensures that data from different sources has a common frame of reference and can be used for comparison.
- Loading (L) involves storing and organizing the transformed data (for example, by arranging it into tables).
