What is the primary goal of data normalization?

The primary goal of data normalization is to reduce data redundancy and improve data integrity. This process involves organizing data within a database in such a way that it minimizes duplication and ensures relationships between different pieces of data are logically consistent. By achieving this, normalization helps in maintaining the accuracy and reliability of data, leading to better database performance and easier data management.

For instance, in a normalized database, repeating groups are eliminated, and each piece of information is stored only once. This structure not only conserves storage space but also helps to avoid anomalies during data operations like updates, deletions, or inserts. Improved data integrity means that the data is more trustworthy and errors are less likely, making it easier to analyze and draw insights from.

The other options do not accurately reflect the primary goal of normalization. While converting non-numeric data into numeric format is essential in certain analytical contexts, it doesn’t directly relate to normalization's goal of reducing redundancy and ensuring integrity. Increasing data size and complexity would contradict the aim of optimization through normalization. Creating visual representations of data pertains to data visualization techniques, which is separate from the normalization process focused on data structure within databases.