Over the years large amounts of data have been stored for business purposes. To turn this data into consistent and accurate information for a specific use, it somehow needs to be transformed.
And so we get to the ETL concept …
Extract, Transform and Load (ETL) refers to a database or data warehousing process that:
- Extracts data from different types of sources (databases, applications or files)
- Transforms data for storing it and use it further for querying and analysis purpose
- Loads it into a final target (database or data warehouse)
The first phase of an ETL process consists in retrieving data from one or more storage sources. Each individual system may have a different format which means that a validation process may take place, as part of the said process.
This extract can be applied on an initial set of data (initial data extract) or can be a repeated process (daily, weekly, monthly, quarterly) that will transfer only the newly created data after the initial extract took place.
The purpose of this phase is to clean the data. The transform phase uses a series of business rules or specific operations to retrieve data from the source. Sometimes transformations may be critical to match the business and technical requirements of the target database. Some data sources need very little or no data processing. Specific operations for transforming data:
- Translating coded values
- Joining data
- Look up and validate the most relevant data (if it was not done in the extract phase)
The load stage sends data to be stored in a warehouse. Some data storages may replace old data with cumulative data. Updating extracted data is normally done on a periodic basis (daily, weekly, monthly, quarterly).
These ETL processes can be set up using almost any programming language, but it can get very complex, so companies prefer to use ETL tools that can communicate with different relational databases, can read different file formats so that, in the end, they can be reused for different projects.
ETL tools usually contain a GUI that helps users transform data easier than writing large programs.
ETL tools available on the market:
- IBM Datastage
- Informatica PowerCenter
- Ab Initio
- Oracle Data Integrator (ODI)
- Microsoft SQL Server Integration Services (SSIS)
- Pentaho Kettle
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