Wrangling
Data wrangling is a process that data scientists and data engineers use to locate new data sources and convert the acquired information from its raw data format to one that is compatible with automated and semi-automated analytics tools.
Data wrangling, which is sometimes referred to as data munging, is arguably the most time-consuming and tedious aspect of data analytics. The wrangler’s goal is to create strategies for selecting and managing large, aggregated datasets in order to produce a semantic data model.
