In this ETL tutorial you will learn to define a complex - but common - ETL scenario involving transforming CSV before writing it to a database.
The CSV data starts in a wide format with columns for each year, which is transformed into a long format by pivoting the data into fewer columns and more rows. This structure aligns better with relational databases and is easier to use in analytical and BI tools.
The process also includes filtering unwanted data and rounding decimals before writing to the database.
Despite the complexity, MapForce simplifies the task with drag-and-drop mapping, dynamic node names, and built-in functions. While this example focuses on CSV data, MapForce also supports XML, JSON, PDF, Excel, EDI, XBRL, and both SQL and NoSQL databases for versatile ETL scenarios.
Watch the previous video in our ETL series: https://youtu.be/ONb97UUNrxE
Learn more about database table actions mentioned in the ETL tutorial: https://www.youtube.com/watch?v=hHQmWdWVvgY
