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/ana/ - Analytics

Data analysis, reporting & performance measurement
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File: 1786627031955.jpg (101.38 KB, 1024x1024, img_1786626993833_bbk5vtxt.jpg)ImgOps Exif Google Yandex

63344 No.2025

I work as a data analyst at a legal services company. Part of my work involves protecting sensitive data during the Test Data Management (TDM) process. Many other departments in the company need test data to develop an application. Copying the production data for test sounds like a good plan. But because the test environment usually has lower cybersecurity requirements, this will cause customer privacy data leaks. So, my job is to mask the sensitive data to protect customer privacy. When it comes to my job, the first thing that comes to many people's minds is that my work involves masking sensitive data. For example, changing the email address from everett@example.com to bourrasque@example.com. Masking data is indeed important, but before we jump to the masking step, there's one basic question:

full read: https://dzone.com/articles/a-practical-pipeline-for-identifying-sensitive-col

63344 No.2026

File: 1786627190662.jpg (155.18 KB, 1024x1024, img_1786627174176_rson5ufk.jpg)ImgOps Exif Google Yandex

u should also run a regex-based scan on the metadata layer of ur databases to catch hidden PII in unstructured fields. scanning just the column names is how most leaks happen when someone adds a new field without updating the schema documentation.



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