Denormalization of a database is most likely to increase the risk of which issue?

Denormalization of a database typically involves consolidating data into fewer tables, which can improve query performance and simplify database access. However, this process can also lead to an increase in redundancy, where the same piece of data is stored multiple times across different tables. This redundancy can contribute to a loss of data integrity, as it becomes challenging to maintain consistency across all instances of the data.

When data is stored in various places, any update, insert, or delete operation must be propagated to all instances of that data. If this propagation is not properly managed, discrepancies can arise, leading to situations where different users or systems access different values for the same data point. This inconsistency compromises the reliability of the data, which is a core aspect of data integrity.

The other options illustrate concerns related to database performance and security but do not directly correlate with the phenomenon of denormalization. While concurrent access and deadlocks pertain to database transactions and their management, and unauthorized access typically concerns access controls and security practices, the central risk associated with denormalization is its effect on data integrity. Thus, it’s clear that denormalization increases the risk of a loss of data integrity due to redundancy and the challenges of maintaining consistent data across the database.