What is ETL?
ETL is a three-phase data integration process that Extracts, Transforms, and Loads data from multiple sources to a consistent data store that is loaded into a data warehouse or other unified data repository.
ETL processing is typically executed using software applications but it can also be done manually by system operators.
How is ETL used?
ETL was introduced in the 1970’s as databases grew in popularity. Over time it became the primary method to process data for data warehousing projects. Through a series of business rules, ETL cleanses and organises data to address specific business intelligence needs. It transforms transactional data to be used in business intelligence software and analytics tools.
Today Modern ETL or ELT is often used within the cloud computing environment. There are different open source products available.
Nowadays ‘classic’ ETL is still used for:
- Extracting data from legacy systems
- Cleansing data to improve quality and consistency
ELT or modern ETL is used for:
- Combining different sets of (big) data and making them available in one unified format for processing through another software tool
- It prepares data fast for access and that makes your BI reports available with the latest data quickly
ETL or ELT?
With the rise of cloud computing the demand for this data integration process shifted from ETL to Extract, Load, Transform. After extracting the data it is loaded as-is into the cloud data warehouse. The data is then transformed using the power and scalability of the target cloud platform.
ETL and Dovetail
Dovetail is an iPaaS. It handles data flow, and it therefore has a lot more functionalities then just ETL or ELT. Dovetail combines application and data integration in one tool, and routing and transforming data can be handled as part of those data integrations.
Do you want to know more about the capabilities of Dovetail?
Or click here if you would like to read more about what iPaaS is.
