Data standardization is closely linked to data transformation and data cleaning. Data transformation involves changing the format, structure, or values of data to make it suitable for analysis or integration. This is a broader concept that includes data standardization as a subset, focusing specifically on bringing data into a uniform format. On the other hand, data cleaning is about correcting or removing inaccurate records from a dataset. It often precedes data standardization, ensuring that the data being standardized is accurate and reliable.

Data governance refers to the overall management of data availability, usability, integrity, and security within an organization. It provides the framework within which data standardization operates, ensuring that the standardized data meets organizational standards and compliance requirements. Metadata management is another related concept, as it involves managing data about data (metadata). Effective metadata management supports data standardization by providing essential information about data sources, formats, and structures.

The ETL (Extract, Transform, Load) process is integral to data standardization. During the 'Transform' phase of ETL, data is standardized to ensure consistency across different datasets. Data integration, which involves combining data from different sources, relies heavily on data standardization to ensure that the merged data is coherent and usable.

Data quality management focuses on maintaining the accuracy, completeness, and reliability of data throughout its lifecycle. Data standardization is a crucial component of data quality management, as standardizing data helps in maintaining these quality attributes. Master Data Management (MDM) involves creating a single, consistent, and accurate view of key business entities. Data standardization plays a key role in MDM by ensuring that data from different sources can be harmonized into a single master dataset.

Data interoperability refers to the ability of different systems and organizations to work together (interoperate) through the exchange and utilization of data. Data standardization facilitates interoperability by ensuring that data exchanged between systems is in a common, understandable format. Data transferability, the ease with which data can be moved from one system to another, is also enhanced by standardization, as consistent data formats simplify the transfer process.