Which of the following best describes data management in GIS?

The best description of data management in GIS focuses on the organization, storage, and preparation of data, which encompasses tasks like summarizing and merging datasets. Effective data management is crucial in GIS because it allows for the integration of various data sources, ensuring that information can be analyzed and visualized effectively. This includes not only combining different datasets to create comprehensive datasets but also organizing data in a way that supports spatial analysis and decision-making.

In GIS, data management involves a wide range of processes, including data cleaning, transformation, and storage strategies that maintain the integrity of the data. By summarizing datasets, users can extract meaningful insights from large volumes of data, while merging datasets allows for the creation of more complete datasets for spatial analysis.

The other choices reflect tasks that are associated with GIS but do not specifically capture the essence of data management. Creating digital graphics and exports pertains more to the visualization aspect of GIS rather than management. Executing spatial analyses focuses on the analytical capabilities of GIS and not on how data is managed. Managing geographic or tabular data, while relevant, is too broad and does not specifically highlight the critical functions of summarizing and merging that are essential to effective data management practices.