Data Warehousing - Data Integration and the Extraction, Transformation and Load (ETL) Processes
3 important questions on Data Warehousing - Data Integration and the Extraction, Transformation and Load (ETL) Processes
What are the three major processes that comprise data integration?
- Accessing data. Make a data source accessible and enable data extraction from it
- Federate data. Integrate data from different sources into a coherent whole that is consistent with the business
- Capture changes. Identify changes/updates in the data source and transfer them to the data warehouse
What are the main data integration technologies used to load data into data warehouses?
- Enterprise application integration (EAI)/service-oriented architecture (SOA). Provide an infrastructure (e.g. APIs or (web)services) that allows applications to push data to the data warehouse.
- Enterprise information integration (EII). Use metadata and XML to combine data from different sources in a coherent view. The data are not necessarily integrated physically.
- Extract, transform and load (ETL). Use data integration tools to extract data from any source, transform it to the proper format and load it into the data warehouse.
Why is ETL important for the data warehousing process?
It provides cleansed and integrated data to the data warehouse, regardless the source the data originates from. While doing this, it keeps track of metadata (changes) and it facilitates all administrative tasks involved (e.g. scheduling, error management, audit logs, statistics).
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