The key differences between Fivetran, MuleSoft, and Xplenty: Hiring a data scientist or engineer can cost up to $140,000 per year —something many businesses can't afford. Still, organizations need to pull data from different locations into a data lake or warehouse for business insights. An Extract, Transform, and Load (ETL) platform makes this process easier, but few organizations have the technical or coding know-how to make it happen.

Companies use their data to accelerate business growth and overtake their competitors. To achieve this, they invest a lot in their ETL (extract-transform-load) operations, which take raw data and transform it into actionable information. It’s no wonder, then, that ETL testing is a crucial part of a well-functioning ETL process, since the ETL process generates mission-critical data.

Learn why ELT is better than ETL and how you can get started with it.