What is one common method of data integration?

The method of Extract, Transform, Load (ETL) processes is a fundamental approach in data integration that involves three key steps. In the extraction phase, data is gathered from diverse source systems, which can include databases, spreadsheets, and application files. Following extraction, the data undergoes a transformation process where it is cleaned, formatted, and enriched as necessary to ensure consistency and quality before it is loaded into a target system.

Once the data is prepared, it is loaded into a destination, often a data warehouse or another database, making it readily accessible for analysis and reporting. ETL processes are widely used because they allow organizations to consolidate large volumes of data from various sources, ensuring that the integrated data is reliable and suitable for business intelligence.

While data warehousing, real-time data processing, and data migration all play significant roles in the broader landscape of data management, ETL specifically focuses on the systematic integration of data from multiple sources into a cohesive repository, meeting the ongoing data needs of organizations.