Sensitive Data Protection

Related topics

• BigQuery works with Sensitive Data Protection From the official documentation: “Uses the Data Loss Prevention API to analyze BigQuery data.”
• Pub/Sub works with Sensitive Data Protection From the official documentation: “Watch the Pub/Sub topic until the DLP job finishes”
• Model Armor works with Sensitive Data Protection From the official documentation: “Model Armor integrates with Sensitive Data Protection to help prevent accidental exposure of private information.”
• Cloud Storage works with Sensitive Data Protection From the official documentation: “Uses the Data Loss Prevention API to analyze a file on GCS.”
• Cloud Run functions works with Sensitive Data Protection From the official documentation: “Create a simple Cloud Function that invokes the DLP API when files are uploaded.”
• Data Catalog works with Sensitive Data Protection From the official documentation: “Send job results to Data Catalog. This feature is [deprecated](/sensitive-data-protection/docs/deprecations).”
• Dataflow works with Sensitive Data Protection From the official documentation: “Use Dataflow and Sensitive Data Protection to securely tokenize and import data from a relational database to BigQuery.”
• Knowledge Catalog works with Sensitive Data Protection From the official documentation: “Send the results of a [BigQuery inspection job](/sensitive-data-protection/docs/inspecting-storage#inspect_a_table) to Knowledge Catalog.”
• Sensitive Data Protection works with VPC Service Controls From the official documentation: “For information about VPC Service Controls support for Sensitive Data Protection, see the [Supported products](/vpc-service-controls/docs/supported-products#table_dlp) table in the VPC Service Controls documentation.”
• AI Protection works with Sensitive Data Protection From the official documentation: “AI Protection integrates with Google Cloud's Sensitive Data Protection (SDP) service to discover, classify, and redact sensitive data going into and out of AI workloads.”
• Cloud Monitoring works with Sensitive Data Protection From the official documentation: “Sensitive Data Protection sends detailed telemetry about your Sensitive Data Protection usage to Monitoring.”
• Gemini Enterprise works with Sensitive Data Protection From the official documentation: “Optional: In the **Sensitive Data Protection policy** section, attach an existing [Sensitive Data Protection](https://cloud.google.com/sensitive-data-protection/docs/sensitive-data-protection-overview) policy to inspect and de-identify data that Gemini Enterprise retrieves…”
• Model Armor depends on Sensitive Data Protection From the official documentation: “For the Sensitive Data Protection advanced mode, Model Armor redacts images only if you configured Model Armor filters with a Sensitive Data Protection inspect template and a Sensitive Data Protection de-identify template.”
• Sensitive Data Protection secures BigQuery From the official documentation: “To help meet compliance requirements, use Sensitive Data Protection to inspect your BigQuery tables and to help protect your sensitive data.”
• Sensitive Data Protection depends on Identity and Access Management From the official documentation: “Sensitive Data Protection uses Identity and Access Management (IAM) to control access to resources.”
• VPC Service Controls secures Sensitive Data Protection From the official documentation: “VPC Service Controls enables you to define a security perimeter around your projects and resources, including Sensitive Data Protection resources.”
• BigQuery is an alternative to Cloud Storage From the official documentation: “The `import_result_sink` must be a Cloud Storage path or a BigQuery table.”
• BigQuery works with Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• BigQuery works with Cloud Storage From the official documentation: “External BigQuery data source backed by Cloud Storage”
• BigQuery works with Dataflow From the official documentation: “Read from BigQuery to Dataflow”
• VPC Service Controls secures BigQuery From the official documentation: “BigQuery data is protected with VPC Service Controls”
• BigQuery works with Knowledge Catalog From the official documentation: “Some Knowledge Catalog functionalities trigger job execution using BigQuery.”
• BigQuery works with Cloud Monitoring From the official documentation: “You can use Monitoring to export your metrics to BigQuery.”
• Cloud Run works with Pub/Sub From the official documentation: “Route Cloud Pub/Sub events to Cloud Run”
• Dataflow works with Pub/Sub From the official documentation: “Pub/Sub notifies Dataflow about the upload.”
• Cloud Run works with Cloud Storage From the official documentation: “Route Cloud Storage events to Cloud Run”
• BigQuery is an alternative to Pub/Sub From the official documentation: “To keep audit logs for a longer period of time or to use more powerful search capabilities, you can route copies of your audit logs to Cloud Storage, BigQuery, or Pub/Sub.”
• Cloud Run functions works with Cloud Storage From the official documentation: “Set up functions in response to events in Cloud Storage:”
• BigQuery works with Cloud Run functions From the official documentation: “BigQuery supports external function calls through Cloud Run functions.”
• Cloud Run depends on Pub/Sub From the official documentation: “Create a Pub/Sub topic that Cloud Scheduler will publish to and the Cloud Run function will subscribe to.”
• Cloud Run functions works with Pub/Sub From the official documentation: “Use Cloud Run functions to publish messages on Pub/Sub.”
• Cloud Storage works with Dataflow From the official documentation: “Write from Dataflow to Cloud Storage”
• Dataflow works with Managed Service for Apache Airflow From the official documentation: “Launch Dataflow pipelines with Cloud Composer”
• BigQuery works with Managed Service for Apache Spark From the official documentation: “This means you can quickly read and write BigQuery data to and from Managed Service for Apache Spark.”
• BigQuery works with Pub/Sub From the official documentation: “createBigQuerySubscription creates a Pub/Sub subscription that exports messages to BigQuery.”
• Cloud Logging works with Managed Service for Apache Airflow From the official documentation: “You can use [Cloud Monitoring](/monitoring/docs) and [Cloud Logging](/logging/docs) with Managed Service for Apache Airflow.”
• Cloud Run functions depends on Pub/Sub From the official documentation: “The Pub/Sub message triggers Cloud Run functions.”
• Cloud Storage works with Managed Service for Apache Airflow From the official documentation: “Managed Airflow associates a Cloud Storage bucket with your environment.”
• BigQuery works with Managed Service for Apache Airflow From the official documentation: “You can use Managed Airflow to orchestrate services in your data pipelines, such as triggering a job in BigQuery or starting a Dataflow pipeline.”
• Cloud Monitoring works with Managed Service for Apache Airflow From the official documentation: “You can use [Cloud Monitoring](/monitoring/docs) and [Cloud Logging](/logging/docs) with Managed Service for Apache Airflow.”
• Cloud Storage works with Identity and Access Management From the official documentation: “To learn how to use IAM with Cloud Storage, see [Using IAM Permissions](/storage/docs/access-control/using-iam-permissions).”
• Cloud Storage works with Pub/Sub From the official documentation: “| **Google Cloud** | Cloud Storage | Pub/Sub |”
• Cloud Storage is an alternative to Pub/Sub From the official documentation: “To keep audit logs for a longer period of time or to use more powerful search capabilities, you can route copies of your audit logs to Cloud Storage, BigQuery, or Pub/Sub.”
• VPC Service Controls secures Cloud Storage From the official documentation: “Storage Transfer Service supports transfers to Cloud Storage buckets protected by VPC Service Controls.”
• BigQuery is an alternative to Managed Service for Apache Spark From the official documentation: “Run queries against your federated data using BigQuery or Managed Service for Apache Spark.”
• Cloud Logging works with Cloud Storage From the official documentation: “Cloud Storage writes various log entries to Cloud Logging in the Google Cloud console.”
• Cloud Logging works with Pub/Sub From the official documentation: “Pub/Sub writes various log entries to Cloud Logging in the Google Cloud console.”
• Cloud Monitoring works with Dataflow From the official documentation: “Dataflow is fully integrated with Cloud Monitoring.”
• Cloud Run is an alternative to Cloud Run functions From the official documentation: “To create remote functions, you must [grant required roles](/bigquery/docs/remote-functions#grant_permission_on_function) to Cloud Run functions or Cloud Run.”
• Cloud Storage works with Managed Service for Apache Spark From the official documentation: “Managed Service for Apache Spark accesses these files on Cloud Storage.”
• Data Catalog is an alternative to Knowledge Catalog From the official documentation: “Use Knowledge Catalog for all new projects to take advantage of AI-powered features and enhanced governance.”
• Dataflow is an alternative to Managed Service for Apache Spark From the official documentation: “For more complex data loads into your Cloud SQL for PostgreSQL database, consider using Dataflow or Managed Service for Apache Spark, which involves creating an ETL process.”
• Identity and Access Management secures BigQuery From the official documentation: “Access to BigQuery data from AlloyDB is managed through IAM.”
• Identity and Access Management secures Cloud Storage From the official documentation: “Cloud Storage uses Identity and Access Management (IAM) for authorization.”
• VPC Service Controls secures Managed Service for Apache Airflow From the official documentation: “Managed Airflow can be selected as a secured service inside a VPC Service Controls perimeter.”
• BigQuery depends on Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• BigQuery works with Gemini Enterprise From the official documentation: “The following table compares the two ways that you can import BigQuery data into Gemini Enterprise data stores.”
• BigQuery works with Identity and Access Management From the official documentation: “BigQuery uses Identity and Access Management (IAM) for authorization.”
• Cloud Logging works with Compute Engine From the official documentation: “Compute Engine sends you Cloud Logging events for scheduled, started, or completed maintenance.”
• Cloud Logging works with Model Armor From the official documentation: “Use Cloud Logging to analyze Model Armor usage patterns, errors, and performance metrics.”