When normalizing data tables, the goal is to:

When normalizing data tables, the primary goal is to decrease the possibility of data anomalies. Normalization is a systematic approach of organizing data to reduce redundancy and dependency by dividing large tables into smaller, more manageable ones while establishing relationships between them. This process plays a crucial role in ensuring the integrity and consistency of data.

By addressing data anomalies—such as update, insertion, and deletion anomalies—normalization ensures that changes to data are straightforward and do not inadvertently affect other data records. For example, when a piece of information needs to be updated, normalization minimizes the risk of updates being made in one place but not in others, thereby preventing inconsistencies.

The other choices do not align with the central objective of normalization. Decreasing the possibility of adding key attributes at a later date is contrary to the aims of normalization; it actually facilitates the addition of such attributes by maintaining a structured approach to data. Increasing the possibility of data anomalies contradicts the fundamental purpose of normalization, which is to promote data integrity and reduce anomalies.