Data mapping
Data mapping for privacy operations
You can't delete what you can't find. A data map is the inventory of where personal data lives—the systems, the tables, the identifier columns, and what you plan to delete versus leave alone.
What a data map contains
Four things, per system:
- The systems that hold personal data—databases, APIs, anything you connect.
- The entities or tables within them that store subject data.
- How a subject is identified—email, phone, external id—and which columns hold it.
- A decision per table: delete, skip, or keep. Decided on purpose, not in a panic.
Schema discovery vs hand-writing
Writing the map by hand is slow and goes stale. A better path: connect to the database, scan the schema, and get a draft map of tables and candidate personal-data fields. A human confirms and corrects; the machine does the exhaustive part. That is what makes the map actually complete.
Why the map is the bottleneck
Without a map, every deletion request turns into archaeology—asking around, grepping code, guessing. With a map, a request becomes a scoped, predictable job. The map is also what makes a DPIA honest: you can only assess data flows you have actually inventoried.
A map that survives
Maps go stale as schemas change. Re-run discovery, flag drift, and re-confirm before trusting a map for production deletion. Treat the map as living infrastructure, not a one-time spreadsheet.
How Erasure fits
Erasure's Data Maps turn the inventory into something that drives real deletion:
- Schema discovery on connected systems, with a draft map to confirm.
- Entity and identifier mappings scoped to each system.
- Dry-run match counts and an execution preview before anything runs.
- Readiness signals so you know when a map is good enough to act on.
Read more
How to Delete a User's Data from PostgreSQL Without Breaking the Database
Deleting one user's data from Postgres means finding every table that references them, handling foreign keys in the right order, and running a safe parameterized DELETE. Here is the working method.
How to Handle Data Deletion Requests: An Operational Guide for Startups
A practical workflow for handling data deletion requests in an Indian startup: intake, verification, fulfilment across systems, timelines, and evidence. No compliance team required.
Data Mapping: Knowing Where Personal Data Lives Before You Need To
Data mapping is the inventory of where personal data lives, what identifiers map to a person, and how to act on it. It is the prerequisite for every deletion request under DPDP.
Right to Erasure Under DPDP: How Deletion Requests Actually Work
The right to erasure under India's DPDP Act is the operational heart of the law. Here is how a deletion request flows from receipt to verification to fulfilment across systems.
Docs
What this does not solve
Maps cover the systems you connect and configure—Erasure does not automatically discover every SaaS tool holding your data. Deletion only reaches connected systems, so the map is only as complete as your setup.
Invite-only beta
Try it on your own stack
Erasure is invite-only in beta. Request an invite and we will walk you through the parts that matter for your product.