Which of the following best describes the purpose of data transformation?

The purpose of data transformation primarily involves formatting data for easier analysis and blending. In a data analysis context, transformation processes convert raw data into a structure that's more appropriate and efficient for analysis. This may include changing data types, aggregating values, normalizing data, or creating derived attributes that can enhance analytical capabilities.

Data transformation improves the accessibility and usability of the data, making it easier to uncover insights and visually represent the information in a way that is more meaningful. It allows for the integration of data from different sources by ensuring that the data conforms to the same standards and formats, thus facilitating a coherent analysis.

While creating diverse data fields, eliminating unnecessary data, and enhancing data security are all important aspects of data management, they serve different purposes than transformation. Creating diverse data fields might be a part of the transformation process, but it doesn't capture the full essence of formatting for analysis. Eliminating unnecessary data can improve efficiency and clarity but does not encompass the broader focus on formatting specifically for analysis and blending. Enhancing data security is crucial for data governance but is not directly related to the transformation process, which primarily focuses on making data ready for analysis.