Which of the following could lead to inconsistencies in data updates?

Data redundancy is the correct choice because it refers to the unnecessary duplication of data within a database or across different databases. When the same data is stored in multiple locations, updates become complicated. For example, if a piece of information is updated in one database but not in the others, it creates inconsistencies. This can lead to confusion and errors when retrieving data, as different users or systems may be referencing different versions of the same data element. Ensuring that data is not redundantly stored is critical for maintaining data integrity and consistency across the organization.

In contrast, minimizing data storage focuses on efficiently storing data, which can help streamline operations but does not inherently impact data consistency. Data modeling is the process of designing the structure of a database to ensure it can efficiently manage data, which helps in maintaining consistency rather than introducing inconsistencies. Data visualization involves the graphical representation of data to aid understanding and is centered on presenting data rather than managing its integrity. Thus, it does not directly contribute to data update inconsistencies.