What is ETL?
ETL means Extract, transform, and load which is a data integration process that include clean, combine and organize data from multiple sources into one place which is consistent storage of data in data warehouse, data lake or other similar systems.
ETL data pipeline will gave us the basic foundation of the data analytics and machine learning workstream. They will do the three main things which are
- First, They will collect the data from the old system and,
- Second, the quality improvement process will be done for the same for making quality data.
- Lastly, the new data will be stored into the new database for the use of analytics
Basically, the ETL make sure the data will be the ready to use in the business needs, for making the process more efficient and qualitative.
What is ETL (Extract Transform Load)?
In analytics and data integration, ETL is an essential procedure. It involves collecting data out of multiple sources, formatting it uniformly, and then feeding it into a target location like a database or data warehouse. In order to provide organizations with actionable insights and the ability to make well-informed decisions, ETL is essential to the consolidation and preparation of data for analysis.
Table of Content
- What is ETL?
- How ETL evolved?
- ETL VS ELT
- How ETL works?
- ETL and other data Integration methods
- Benefits and challenges of ETL
- ETL tools
- The Future of Integration-API’s using EAI
- Conclusion
- Frequently Asked Questions on What is ETL?
Contact Us