Data wrangling is a process of cleaning, manipulating, organizing, and transforming raw data into a usable format. It involves selecting, combining, and importing raw data from multiple sources, as well as cleaning, reformatting and transforming the data into a structured, machine-readable format. Once the data is in a structured format, it can be used for data analysis and research. Data wrangling also involves identifying and handling errors and inconsistencies in the data. Additionally, it requires creating and modifying variables and adding metadata to the dataset.