Structured data processing improves Enterprise Data Loss Prevention (E-DLP) detection accuracy when inspecting .csv, .docx, .tsv, .xls, and .xlsx file types that support tabular data formats. This feature implements intelligent column analysis for Enterprise DLP by introducing advanced header detection techniques that treat column headers as proximity keywords that influence detection confidence. Additionally, structured data processing allows Enterprise DLP to use machine learning techniques to handle cases of misspelled or missing headers more effectively. Together, these improvements increase the quality of detections, address limited file format support, and resolve inconsistent header prediction by the Enterprise DLP cloud service. Structured data processing strengthens your organization's data protection strategy by addressing specific challenges related to structured data formats to improve detection accuracy across various data loss scenarios, and help you meet compliance requirements to protect value personally identifiable information (PII) when scanning structured file types.

For example, consider the example .xlsx file below with three columns containing sensitive data. You formatted column A correctly. However, you formatted columns B and C incorrectly because you misspelled the header for column B and did not include a column header for Column C. With structured data processing, Enterprise DLP can now accurately detect and render verdicts on data in columns B and C.