What is the expected outcome of data normalization?

The expected outcome of data normalization is improved data integrity and less redundancy. Normalization is a process used in database design aimed at organizing data in such a way that dependencies are properly established, which helps to reduce data anomalies. By minimizing redundancy, normalization ensures that each piece of data is stored only once, which enhances the consistency and accuracy of the data across the database.

When data is structured through normalization, it reduces the risk of having multiple instances of the same data that might not match, thereby ensuring that updates, deletions, or insertions to the data do not create discrepancies. This strengthened integrity is critical for businesses that depend on accurate data for decision-making, reporting, and analysis.

The other options present potential scenarios that arise from poor data management practices, such as increased complexity, creation of data silos, or reduced access to data, which are typically the opposite of what normalization aims to achieve. The primary focus of normalization is to simplify data structures while maintaining essential relationships, ultimately leading to enhanced data reliability.