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Google Cloud
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  • Console
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  • Start free
  • Discover
  • Product overview
  • Plan your data risk management strategy
    • Evaluate your data risk management needs
    • Learn about your data through discovery and inspection
    • Recommended strategies for mitigating data risk
  • Release notes
  • Pricing
  • Locations
    • Global and regional endpoints for Sensitive Data Protection
    • Sensitive Data Protection locations
    • Specify a processing location
  • Service method types
  • Supported file types and scanning modes
  • Get started
  • Quickstarts
    • Inspect text using the command-line tool
    • Inspect text using a JSON request
    • Schedule an inspection scan
    • Create an inspection template
    • De-identify and re-identify sensitive text
  • Google Cloud Skills Boost labs
  • Detect sensitive data
  • Discover and profile data resources
    • Overview of data profiles
    • Common discovery enablement scenarios
    • Profile your data
      • Profile a single data resource
      • Profile BigQuery data
        • Estimate BigQuery data profiling cost
          • Estimate the cost of profiling BigQuery data in a project
          • Estimate the cost of profiling BigQuery data in an organization or folder
        • Profile BigQuery data in a project
        • Profile BigQuery data in an organization or folder
      • Profile Cloud SQL data
        • Profile Cloud SQL data in a project
        • Profile Cloud SQL data in an organization or folder
        • Manage connections
      • Profile Cloud Storage data
        • Profile Cloud Storage data in a project
        • Profile Cloud Storage data in an organization or folder
      • Profile Vertex AI data
        • Sensitive data discovery for Vertex AI training data
        • Profile Vertex AI data in a project
        • Profile Vertex AI data in an organization or folder
      • Profile Amazon S3 data
        • Sensitive data discovery for Amazon S3 data
        • Profile Amazon S3 data
      • Profile Azure Blob Storage data
    • Report secrets in environment variables to Security Command Center
    • Grant data profiling access to a service agent
    • Manage data profiles
    • Control IAM access to resources based on data sensitivity
    • Send discovery insights to other services
      • Enable discovery actions
      • Send data profiles to Security Command Center
      • Receive and parse Pub/Sub messages about data profiles
      • Tag tables in Data Catalog based on insights from data profiles
      • Add Dataplex Universal Catalog aspects based on insights from data profiles
    • Analyze and visualize data profiles
      • Visualize data profiles in the discovery dashboard
      • Analyze data profiles
    • Remediate findings from the data profiler
    • Manage scan configurations
    • Troubleshoot issues with the data profiler
    • Metrics reference
    • Data risk and sensitivity levels
  • Inspect for sensitive data
    • Inspect data stored in Google Cloud
    • Inspect data from any source
      • Inspect unstructured text synchronously
      • Inspect structured text synchronously
      • Inspect an image synchronously
      • Asynchronous inspection overview
      • Inspect data from any source asynchronously
    • Quote the sensitive data in the results
    • Work with inspection results
      • Actions
      • Send inspection results to Dataplex Universal Catalog as aspects
      • Send inspection results to Data Catalog
      • Send inspection results to Security Command Center
      • Analyze and report on inspection findings
      • Query inspection findings in BigQuery
      • Parse findings stored as Protobuf text
    • Jobs and job triggers
      • Overview of jobs and job triggers
      • Create and manage jobs and job triggers
    • Web-based inspection demonstration app
  • Configure detection
  • Templates
    • Overview of templates
    • Create inspection templates
  • InfoTypes and infoType detectors
    • Overview of infoTypes and infoType detectors
    • Built-in infoType detectors
      • List built-in infoType detectors
      • InfoType detector reference
    • Custom infoType detectors
      • Overview of custom infoType detectors
      • Create a regular custom dictionary detector
      • Create a large custom dictionary detector
      • Create a custom regex detector
      • Custom infoType examples
    • Manage infoTypes through the Google Cloud console
    • Modify infoType detectors to refine scan results
  • Match likelihood
    • Likelihood overview
    • Customize match likelihood
  • Mask and de-identify data
  • Overview
  • Transformation methods
    • Transformation reference
    • Text classification and redaction
    • Date shifting
    • Generalization and bucketing
    • Pseudonymization
  • De-identify sensitive data
    • De-identify data stored in Google Cloud
      • Overview
      • Through the Cloud console
      • Through the DLP API
      • Transformation details reference
    • De-identify data from any source
      • De-identify text or tabular content
      • Examples of text redaction
      • Examples of tabular data de-identification
      • Image inspection and redaction
      • Redact sensitive data from images
  • Create a de-identification template
  • Create a wrapped key
  • De-identify BigQuery data at query time
  • De-identification and re-identification of PII in large-scale datasets
  • Redact sensitive data from PDF files
  • Analyze re-identification risk
    • Overview of re-identification risk analysis
    • Re-identification risk analysis techniques
    • Compute k-anonymity for a dataset
    • Compute l-diversity for a dataset
    • Compute k-map for a dataset
    • Compute δ-presence for a dataset
    • Compute numerical and categorical statistics
    • Visualize re-identification risk using Looker Studio
  • Connect to other services
  • Use Sensitive Data Protection with BigQuery
  • Use Sensitive Data Protection with Cloud Storage
    • Use Sensitive Data Protection with Cloud Storage
    • Automate the classification of data uploaded to Cloud Storage
  • Send inspection results to Data Catalog
  • Send inspection results to Security Command Center
  • Monitor your usage with Cloud Monitoring
  • Use Sensitive Data Protection with AWS S3
  • Use Sensitive Data Protection with JDBC Databases
  • Use Sensitive Data Protection with Apigee
  • Use Sensitive Data Protection with Data Fusion
  • Build a secure anomaly detection solution using Dataflow, BigQuery ML, and Sensitive Data Protection
  • Troubleshoot
  • Troubleshoot issues with the data profiler
  • Control access