SQL Data Discovery and Classification (DSPM)

Discover and Classify sensitive data in SQL Databases

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Table of Contents

TL;DR

SQL Data Discovery and Classification ≠ optional – it is table‑stakes for GDPR, HIPAA, PCI DSS and every modern data‑governance framework.
Native Microsoft tooling (SSMS & Azure Portal) is a strong starting point—automatic column scans, built‑in labels, exportable reports.‍
Gaps remain: pattern‑based only, no remediation, blind to cross‑database exfiltration, minimal API automation.
Third‑party platforms add richer taxonomies, AI‑driven patterning, and workflow automation, but often stop at discovery.
Strac unifies SQL Data Discovery and Classification with active DLP, giving real‑time remediation (mask, encrypt, redact, revoke) plus agentless, self‑hosted scanners for AWS RDS, Azure SQL, on‑prem SQL Server and more.

✨ SQL Data Discovery and Classification (DSPM) – A Visual Overview

Think of SQL Data Discovery and Classification as the “x‑ray” that shows exactly where sensitive data lives (columns, tables, result sets) and how critical it is (labels, ranks). Without that visibility, any downstream DLP or access‑control is guesswork.

Strac Cloud DSPM (Data Security Posture Management) = Data DIscovery and Classification

Why SQL Data Discovery and Classification Matters for Modern Security

SQL Data Discovery touches every pillar of a security program:

Compliance evidence – auditors want proof that you know which columns hold PHI/PCI and that those columns are protected.
Risk scoring – mapping crown‑jewel data to exposure paths drives smarter investment.
Incident response – faster blast‑radius analysis when a credential is stolen.
Least‑privilege enforcement – sensitivity labels tie into Dynamic Data Masking or Purview policies to block unauthorized selects.Microsoft Learn

Gaps in Native SQL Data Discovery and Classification Features

Name‑pattern bias – Columns called card_number are caught; cn or JSON blobs are missed.
No OCR or LLM context – Free text and images inside varbinary/BLOB columns stay invisible.
Limited automation – T‑SQL / PowerShell APIs exist but lack webhook‑ready events; CI/CD pipelines still need glue code.
No response actions – Discoveries do not automatically mask, tokenize, or block downstream access.

Result: security teams still export CSVs, open tickets, and hope developers fix things.

Evaluating Third‑Party SQL Data Discovery and Classification Tools

Platforms such as Netwrix DSPM, Secoda and others add:

AI/ML pattern engines to lower false positives.
Data catalogs & lineage for governance teams.
Cross‑source dashboards (SQL, NoSQL, SaaS).

Yet most vendors stop at discovery—they surface problems but hand remediation back to you

✨ How Strac Reinvents SQL Data Discovery and Classification

Strac ties together discovery and real‑time DLP, eliminating the hand‑off gap.

Implementation Roadmap for Effective SQL Data Discovery and Classification

Inventory every SQL data store (prod, staging, BI replicas).
Baseline with native sql data discovery and classification scan—export the report.
Prioritise high‑risk labels (e.g., Highly Confidential + Financial).
Deploy Strac scanner in a read‑only role; schedule nightly incremental scans.
Enable auto‑remediation rules (mask, redact) for Tier‑1 labels.
Connect Strac DLP to email, SharePoint, BI and browser to enforce the same policies in transit.
Review metrics weekly: newly discovered columns, remediated incidents, policy drift.

FAQs – SQL Data Discovery and Classification

SQL Data Discovery and Classification: Is sampling 10 K rows per column really enough?

Industry baseline is 100 representative values per column; beyond that, accuracy plateaus while costs rise sharply. Strac samples adaptively—scaling up on free‑text columns, down on deterministic fields—to balance accuracy and cost.

SQL Data Discovery and Classification: Can’t I just use regex everywhere and skip ML?

Regex excels for SSNs or credit‑cards but fails on context‑driven data like “Diagnosis: Asthma.” Strac blends deterministic regex with lightweight LLM context scoring so you don’t choose between accuracy and budget.

SQL Data Discovery and Classification: Will running Strac scanners impact query latency?

No. Scans run against read replicas or snapshot copies; production workloads stay isolated.

SQL Data Discovery and Classification: How does Strac compare to Microsoft Purview?

Purview labels and audits but relies on manual enforcement. Strac acts—masking, blocking, or tokenising data automatically across SQL, SaaS and endpoints, while still ingesting Purview labels for continuity.

(More questions? Ping us or explore the full connector list on our integrations page.)

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Sharepoint DLP Use Cases

Practical Scenario

A hospital’s billing and administrative teams use SharePoint Online to store patient invoices, medical reports, and insurance forms. While collaborating with external insurance providers, a staff member accidentally updates the permissions on a SharePoint document library to “Anyone with the link,” exposing potentially thousands of patient files containing PHI.

How Strac's Sharepoint DLP Helps

Continuous Data Discovery: Strac automatically scans existing and newly uploaded documents, identifying PHI (e.g., medical record numbers, Social Security Numbers).
Classification & Labeling: Once identified, files are labeled (e.g., “HIPAA Sensitive”), ensuring that administrators know which documents require the highest level of protection.
Visibility into Access: Strac provides real-time insight into who has access to these sensitive documents. Administrators can instantly see if unauthorized users or broad groups have viewing rights.
Revoke Public Links: If a file is publicly accessible, Strac immediately revokes those links and restores restricted access.
Alerts & Quarantines: When someone attempts to share PHI externally, Strac can alert admins, quarantine the file for review, or completely block the action.
Audit-Ready Reports: All actions are logged, enabling quick incident response and demonstrating HIPAA compliance for audits.

Practical Scenario

A mid-sized investment firm uses SharePoint to collaborate on various client files, including:

Credit card statements (subject to PCI-DSS)
ID documents (Driver’s Licenses, Passports, etc.) used for KYC (Know Your Customer) verification
Banking information such as account and routing numbers

An associate accidentally shares a SharePoint folder containing these files with a newly onboarded client who does not require access to all confidential documents. This folder is also accessible to several internal teams outside the immediate project, creating multiple potential exposure points.

How Strac's Sharepoint DLP Helps

Comprehensive Data Discovery: Strac scans both existing and newly uploaded documents in SharePoint for sensitive information such as credit card numbers, bank account details, and ID documents (Driver’s License, Passport formats).
Classification & Automated Labeling: Once identified, Strac applies meaningful labels (e.g., “PCI-DSS Sensitive,” “PII – ID Documents,” “Banking Info”) to ensure these files stand out and are subject to stricter security rules.
Visibility into Access: Strac provides an immediate view of who currently has access to these sensitive files. This allows admins to spot situations where external clients or internal teams unnecessarily have permissions.
Public Access Revocation: If a labeled document (e.g., containing card data or ID scans) is found to be publicly shared or too broadly accessible, Strac automatically revokes these links or permissions, aligning access with the principle of least privilege.
Alerts, Quarantines, and Blocks: When a user attempts to share a labeled document with outside domains—or with an entire department—Strac alerts administrators or quarantines/blocks the file share, depending on policy settings.
In cases where the share is intentional but needs review, admins can approve or deny the request within Strac’s dashboard.
Audit & Compliance: Every sharing event, label assignment, and access revocation is logged, creating a detailed audit trail. This helps demonstrate compliance with PCI-DSS, KYC, AML, and other regulatory requirements.
Automatic reporting simplifies any regulatory or internal compliance audit, reducing the administrative burden on security and compliance teams.

Practical Scenario

A software company keeps source code, product roadmaps, and design specs in SharePoint. Several teams—including external contractors—use the same SharePoint site. A developer accidentally grants a large group, including some non-disclosure–exempt contractors, access to a folder containing patent-pending code.

How Strac's Sharepoint DLP Helps

Holistic File Scanning: Strac inspects documents, PDFs, and archives for code snippets, system designs, and proprietary business terms to detect potential IP.
Intelligent Labeling: Documents identified as containing IP or trade secrets are automatically classified (e.g., “Proprietary IP”), reinforcing the need for restricted sharing.
Real-Time Access Insights: With Strac, administrators can instantly see who has access to IP-tagged files, enabling them to remove unauthorized users or reduce permission scopes.
Immediate Link Removal: If a contractor or external partner is mistakenly granted access to IP, Strac revokes public or unauthorized sharing before the files can be downloaded.
Alerts & Blocking: Strac’s policies can be configured to alert security teams or block external sharing attempts for files containing proprietary content.
Incident Response & Auditing: Detailed logs of every share request, label change, and access revocation aid in quick incident resolution and help prove due diligence if legal issues arise.