Data transformation is the process of converting sets of data values from a source format to a format consistent for a destination data system. Data element to element mapping can be complicated and requires complex transformations that require lots of rules, which is why successful analysts use these tools to help simplify the process. This on-going process of shaping, standardizing and enriching data to conform to the right analytic outputs, has long been considered tedious, time-consuming, “janitorial” work. Worse yet, when it comes to complex or large volumes of data, the work is relegated to the small number of valuable resources with advanced data science skills, regardless of whether they have the business context or not. In short, this process has historically been fraught with roadblocks and frustrations, often consuming way more time than the actual analysis. Until recently there haven’t been a lot of data transformation tools available help solve the challenges of IT organizations.