Data preparation, also known as data wrangling, is a data management process that involves combining data from disparate sources, profiling it to understand issues and potential improvements, and then cleaning and enriching it to prepare it for use by downstream applications, most commonly, business analytics.
Traditionally, IT has been the gatekeeper when it comes to data. When business users needed to use a data source for business intelligence, they had to wait on IT to code routines to move and extract the data, standardize, deduplicate, correct, and otherwise clean it, and then provide an enriched dataset ready for analysis. As a result, in many enterprises today, time to analytics is measured in quarters or years.
You need a better, modern approach to data preparation.