Scan the relevant estate
The plan prioritizes systems and data stores by exposure and importance. Patterns, metadata, schema, samples, and configuration provide evidence without copying more personal data than required.
Source to evidence
DPDP data discovery
Create a usable inventory of personal data, its purpose, owner, source, destination, access, retention, and known gaps.
Personal-data discovery with context for action
Know where personal data lives, why it is used, and who owns it.
Discovery creates a working inventory across databases, warehouses, lakes, files, SaaS platforms, applications, logs, backups, reports, and data movement. BluePi combines automated scanning with metadata and owner review.
A useful record carries purpose, sensitivity, subject type, source, processing, sharing, access, residency, retention, lineage, owner, and confidence. Unknowns remain visible for follow-up.
Validate with accountable owners
Technical findings are reviewed with application, data, security, privacy, and business owners. False positives, ambiguous fields, derived data, and undocumented transfers receive a resolution record.
Feed control implementation
The inventory supports access review, retention, deletion, consent mapping, rights handling, lineage, security remediation, and evidence reporting through named downstream work.
When this is the right starting point
- Data maps depend on spreadsheets and memory
- Teams cannot locate all copies of sensitive attributes
- Backups, exports, reports, and logs sit outside the inventory
- Control programs lack a reliable system and owner map
Good fit
One operating workflow has a named owner, a measurable baseline, and users who can judge whether the result improves.
Poor fit
The request is capacity-only staffing, an unowned demonstration, or a broad transformation without a first decision and finish condition.
Evidence produced during delivery
- Baseline and decision definition
- Data and system-boundary map
- Evaluation or reconciliation result
- Runbook and ownership transfer
System detail
Open the part you need. Each section expands into the full delivery scope for that step.
01Find data across the estate
Discovery covers operational applications, files, analytical platforms, reports, interfaces, archives, and third-party processors.
02Record enough context to act
Each record connects the data to purpose, owner, source, destination, users, access, retention, and downstream processing.
- System and file discovery
- Personal-data classification
- Flow and processor mapping
- Ownership and gap register
03Support the next controls
The inventory provides an implementation base for consent, retention, rights requests, access, and security work.
FAQWhat is DPDP data discovery?
An inventory your owners can act on: every personal-data store listed with its purpose, owner, source, destination, access, retention, and known gaps, verified against deployed systems rather than policy documents.
FAQWhy do spreadsheets fail as a personal-data inventory?
A spreadsheet says where personal data should be, while deployed copies spread through logs, exports, test stores, and integrations. Discovery follows the running systems rather than the intended design.
Start with one operating workflow.
We will review the owner, the baseline, the data path, the system boundary, and the route to go-live.
Discuss one workflow