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Normalization is a process used in relational database design aimed at reducing data redundancy and improving data integrity by organizing data into multiple related tables. While normalization has many benefits, a significant drawback is that it can make queries less intuitive and potentially more expensive in terms of performance.

When a database is normalized, data is spread across various tables, which often requires complex joins to retrieve related information. These joins can lead to queries that are more complicated in their structure, making them harder to write and understand. Additionally, because these queries often involve retrieving data from multiple tables, they can be slower and require more processing power compared to querying a single table with denormalized data.

In contrast, while normalization reduces data redundancy, it does not simplify data storage processes. Instead, it can complicate the schema design and the way developers interact with the data. It also maintains consistency and integrity by employing foreign keys and other constraints, which is contrary to reducing transaction consistency. Thus, the selection of this specific answer highlights a key challenge that arises when a database is highly normalized, impacting both the performance of queries and the overall user experience when interacting with the data.

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