What is data merging?

Data merging refers to the process of combining two or more data sets into a single, unified data set. This is often necessary in data analysis when multiple sources of information need to be consolidated to create a comprehensive view of the data. By merging data sets, analysts can enhance their analysis by incorporating additional information, eliminating redundancies, or simply combining related data that resides in different files or formats.

This process is crucial in scenarios such as preparing data for analysis, generating reports, and conducting comprehensive data profiling. When done correctly, data merging allows for a richer dataset that can lead to more informed insights and better decision-making.

The other options refer to different data management techniques. For instance, separating data into different categories pertains more to classification tasks rather than combining them. Validating data involves checking for accuracy and consistency but does not involve merging or combining sets. Lastly, transforming raw data into a cleaned format relates to preprocessing, which is an essential aspect of data preparation but distinct from the specific action of merging data sets.