Data Discovery for Personal Data and Privacy Risk

Espresso Data Privacy Data Discovery creates transparency across files, databases and connected systems. It helps organizations find personal data, identify risk, review findings and prepare controlled deletion or remediation actions.

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Find personal data before it becomes a privacy risk

Many organizations do not know exactly where personal data is stored. It may be distributed across file shares, databases, office documents, business applications and cloud-connected systems. Without reliable visibility, privacy work becomes manual, slow and difficult to prove.

Espresso Data Privacy Data Discovery turns this search into a controlled operating process. It detects personal and sensitive data, shows where findings are located, supports review decisions and provides evidence for privacy, audit and management reporting.

Data sources and detection

Data Discovery is designed for self-hosted environments and supports a practical starting scope that can be expanded step by step. Typical sources include local file systems, PostgreSQL, MySQL/MariaDB, Microsoft SQL Server and Microsoft 365 data such as SharePoint or OneDrive for Business.

  • Files and documents are scanned for structured patterns, keywords, context and, where required, OCR-based text extraction.
  • Database tables and fields can be scanned with metadata that preserves the origin of each finding.
  • Microsoft 365 sources can be connected to discover personal data in selected sites, drives or folders.
  • Local processing keeps sensitive content under the customer's control wherever possible.

Review, suppression, measures and audit

A technical finding is not automatically a final privacy decision. Data Discovery therefore includes a review process where users can confirm findings, mark false positives or suppress recurring known noise. This improves quality and keeps the workflow transparent.

  • Findings show detected personal data, source, location, detector, confidence and risk context.
  • Review separates real findings from false positives and documents the decision.
  • Measures turn relevant findings into operational actions such as delete, mask, clarify or check access.
  • Audit and reports provide traceability for privacy teams, management and external review.

The missing step before Data Deletion

Data Deletion remains the central execution capability of Espresso Data Privacy. Data Discovery strengthens it by answering the question that comes first: where is personal data stored and which data locations require action?

The practical workflow is simple: discover personal data, assess the risk, review the findings, define measures and then orchestrate deletion or other remediation steps with evidence. This turns data protection from a manual search exercise into a repeatable process.

Start small, then expand

A typical rollout starts with a clear scope such as one file share, one database schema or one Microsoft 365 site. The first scan creates transparency quickly. Results are reviewed together, risks are prioritized and the regular discovery process can then be expanded to additional sources.

  • Select a relevant first data source.
  • Run a first scan with a controlled scan profile.
  • Review findings and identify false positives.
  • Prioritize risks and measures.
  • Connect the results to deletion, reporting or operational follow-up.


Continue with the Data Deletion concept or explore the Solution Documentation.