Standardization in data management aims to:

Standardization in data management aims to:

• A. Add new data fields
• B. Ensure data conforms to reference data codes
• C. Improve data visualization
• D. Delete obsolete records

Answer: (B)

Standardization in data management is crucial as it focuses on ensuring that data adheres to specific formats, values, and coding systems, known as reference data codes. This process helps in maintaining consistency and accuracy across datasets, facilitating better integration and analysis. By standardizing data, organizations can ensure that it is interoperable and that different systems can communicate effectively, reducing discrepancies and misunderstandings that could arise from data that is not uniform. Standardization allows for streamlined data processing and makes it easier to compare data from different sources, leading to improved data quality overall. It also simplifies regulatory compliance and reporting, as standardized data can be easily aligned with external requirements. While adding new data fields, improving data visualization, and deleting obsolete records are important aspects of data management, they do not directly relate to the primary goal of standardization, which is to align data with established standards and coding systems.

Standardization in data management is crucial as it focuses on ensuring that data adheres to specific formats, values, and coding systems, known as reference data codes. This process helps in maintaining consistency and accuracy across datasets, facilitating better integration and analysis. By standardizing data, organizations can ensure that it is interoperable and that different systems can communicate effectively, reducing discrepancies and misunderstandings that could arise from data that is not uniform.

Standardization allows for streamlined data processing and makes it easier to compare data from different sources, leading to improved data quality overall. It also simplifies regulatory compliance and reporting, as standardized data can be easily aligned with external requirements.

While adding new data fields, improving data visualization, and deleting obsolete records are important aspects of data management, they do not directly relate to the primary goal of standardization, which is to align data with established standards and coding systems.