Which process is primarily concerned with transforming unstructured data into a format understandable by computers?

The correct choice focuses on natural language processing (NLP) because it specifically deals with the transformation and understanding of unstructured data, such as text and speech, into a form that can be effectively utilized by computers. NLP employs various techniques and algorithms to analyze and interpret human language, enabling computers to comprehend and generate language in a meaningful way.

For instance, in healthcare, NLP can be applied to extract relevant information from clinical notes, patient records, or research articles that exist in an unstructured format. This capability is crucial for improving data accessibility, aiding decision-making, and enhancing patient care.

Other processes, while important in the realm of data management and analysis, do not specifically focus on converting unstructured data into a computable format. Data analysis generally involves the examination of datasets to draw conclusions but is not limited to unstructured data. Normalization pertains to organizing data within databases to reduce redundancy but does not directly address unstructured data processing. Data warehousing involves the storage and retrieval of structured data from various sources but lacks the focus on transforming unstructured content into structured formats for computational use.