Which process involves a company examining its data against business expectations?

The process of data gap analysis involves a company assessing its existing data in relation to its business expectations. This practice helps organizations determine whether they have the necessary information to meet their goals and objectives effectively. By evaluating where their data stands compared to what is needed, businesses can identify deficiencies and areas where enhanced data collection or management processes may be necessary.

This type of analysis is crucial for strategy development and operational improvement, as it enables companies to understand their current data capabilities and make informed decisions to align their data resources with their business strategies. By doing so, organizations can ensure they are not only collecting the right types of data but also using it effectively to drive business outcomes.

In contrast, while data modeling creates a conceptual framework for data and helps in organizing information, it does not directly assess alignment with business expectations. Database management focuses on the effective storage and retrieval of data, and data mapping relates to the process of connecting and structuring data elements but does not specifically evaluate them against business goals. Thus, data gap analysis is the most suitable process for examining data in the context of business expectations.