What is Data Standardization?

Data Standardization refers to the process of ensuring data consistency and predefined formats across various datasets within an organization. This process is crucial for maintaining data quality, as it enables various systems and users to interpret and utilize data uniformly. By standardizing data, organizations can reduce discrepancies that might arise from variations in formats, definitions, or structures used when data is collected and stored.

This practice involves establishing rules and guidelines that dictate how data elements are defined, formatted, and categorized. For example, standardizing dates into a specific format (like YYYY-MM-DD) or ensuring consistent use of units of measure (such as using metric or imperial uniformly) ensures that all stakeholders can trust and effectively work with the data.

The other choices do not align with the definition of data standardization. Summarizing large datasets relates more to data aggregation, while deleting redundant data pertains to data deduplication. Organizing data in folders pertains to data storage and file management rather than the actual content or structure of the data itself. Therefore, the emphasis on consistency and formats encapsulates the true essence of data standardization, validating the selected answer's accuracy.