What does data abstraction refer to?

Data abstraction refers to the process of simplifying complex data structures to make them easier to understand and use. This concept is foundational in data management and computer science because it allows users to interact with datasets without needing to understand the intricate details of how those data are organized or processed. By abstracting data, essential characteristics and functionalities are emphasized while hiding the underlying complexity, which ultimately aids in easier data manipulation and retrieval.

For instance, in a database, a user may only need to interact with a simple interface that allows for queries and updates, rather than dealing directly with the underlying tables and relationships. This abstraction facilitates more efficient programming and application development, as developers can focus on higher-level operations rather than the nitty-gritty details of data storage.

The other options relate to important concepts in data management but do not accurately define data abstraction itself. Enhancing data security measures, documenting data management practices, and promoting data sharing are all significant aspects of managing data, yet they do not capture the essence of simplifying and hiding complexity that is intrinsic to data abstraction.