Data classification is the process of tagging data according to its type, sensitivity, and value to the organization. Data transformation is the process of changing the structure and format of data to make it usable for analysis and visualization. Both processes are important for data security and compliance, but they also pose some challenges.
One of the challenges is to ensure that the organization's data classification policies are preserved during the process of data transformation. This means that the data should retain its original classification level and labels after it is transformed, and that the appropriate controls and protections are applied to the transformed data.
The best way to ensure this is to implement classification labels in metadata during data creation (D).
Metadata is data that describes other data, such as its source, format, content, and context. By adding classification labels to metadata, the data can be easily identified and tracked throughout its lifecycle, including during data transformation. The labels can also help enforce the proper access rights and encryption standards for the data, regardless of its state or location.