A rather small financial institution experienced a problem in top-level decision making due to the lack of visibility in the existing data and inability to find needed documents due to the absence of structure in existing data. This triggered implementation Data Management System (DMS). A consulting firm was tasked to come up with the solution that will fulfil their needs.
The project was divided into 3 parts:
Step 1. Elaboration of standard procedures and data discovery.
Step 2. Data classification and privacy data identification.
Step 3. Data migration to DMS.
The project started with the definition of the standard rules to be adopted across the DMS. Then consultants were challenged with data discovery and audit. Using the native tools they've been able to manually process more than 2.5 million documents in 2 weeks. They have been able to extract metadata, find similarities and identify duplicates.
The next step was to classify the data and detect privacy data. The main challenge was to run this process on unstructured data. At this point consultants adopted INDICA which is perfect with unstructured data. After a month long the results were the following:
- In case INDICA was implemented at the Step 1 it would save up to at least 4 weeks of manual data discovery.
- Auto - classification was done on the background, hence easier to allocate documents to be migrated.
- The solution provides the possibility to detect what is the file & who can take action
- Discovery of privacy issues is done automatically.
- Not applicable to current project, but INDICA eliminates the need for a DMS and data migration as needed files can be found within the existing file structure.
Finally the customer adopted 2 INDICA solutions: INDICA GDPR for privacy data discovery and INDICA Enterprise Search for quick access to the relevant data.