What is the term for converting or transforming data into a more useful structure?

Data transformation is the process of converting or transforming data into a more useful structure. This involves altering the data’s format, structure, or values to make it more appropriate for analysis or further processing. It may include operations such as normalizing data, aggregating it, or converting it into a different format. The primary goal is to enhance the usability of the data for specific analytical needs or to prepare it for more complex analysis.

While data cleaning, which is often a preliminary step, focuses on correcting errors, removing duplicates, or handling missing values, data transformation dives deeper into adjusting and reformatting data. Data wrangling, which can be closely related, involves a broader set of practices that include data cleaning and transformation, among other steps, to reshape the data into a desired format. Categorical data refers to variables that represent types or categories of information and is not a process related to transforming data.