BigID automated the process of Data Subject Requests (DSR) and data discovery of databases containing personally identifiable information (PII).
I worked on a project using BigID for automating DSR and data discovery for PII. The project was divided into several phases. The first phase involved business contact and socialization, where we reached out to different stakeholders and learned about their databases and which tables contained the most PII. The next phase was the technical gathering phase where we understood the IP address, tables, port numbers, and whether the IP was dynamic or static. The subsequent phase was the build and connectivity phase where we created data sources from those databases.
The most valuable part of BigID was the scan and result phase, which provided nearly accurate results of the databases containing PII numbers and the metadata of the PII present in the database. It also described what the tables contained. We had the asset owners verify the results, and the next phase was the test phase where we collected primary data sample test cases such as email IDs or employee IDs to conduct test DSRs on the process. When scanning results were correct and accurate, we closed them out.
BigID should focus more on the unstructured data part because many organizations have significant amounts of unexplored unstructured data containing large quantities of PII that they are not even aware of. If BigID could scan unstructured data in a seamless way as they do with structured data, it would be very useful for companies to discover the PII data hiding within unstructured data.