policy tags

Related topics

• Data Catalog works with policy tags From the official documentation: “You can move a policy tag only through the Data Catalog `PolicyTagManager.UpdatePolicyTag` method.”
• policy tags is part of BigQuery From the official documentation: “Policy tags in BigQuery let you enforce [column-level access control](/bigquery/docs/column-level-security-intro) and [dynamic data masking](/bigquery/docs/column-data-masking-intro) on sensitive table data.”
• policy tags configures dynamic data masking From the official documentation: “Policy tags in BigQuery let you enforce [column-level access control](/bigquery/docs/column-level-security-intro) and [dynamic data masking](/bigquery/docs/column-data-masking-intro) on sensitive table data.”
• policy tags works with Sensitive Data Protection From the official documentation: “To determine the types of sensitive data that you have and which columns need policy tags, consider generating profiles about your data across an organization, folder, or project by using Sensitive Data Protection.”
• BigQuery works with Sensitive Data Protection From the official documentation: “Uses the Data Loss Prevention API to analyze BigQuery data.”
• 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 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.”
• Dataflow works with Pub/Sub From the official documentation: “Pub/Sub notifies Dataflow about the upload.”
• Pub/Sub works with Sensitive Data Protection From the official documentation: “Watch the Pub/Sub topic until the DLP job finishes”
• BigQuery is an alternative to Google Cloud Storage From the official documentation: “The training data can be either a CSV file in Cloud Storage or a table in BigQuery.”
• 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.”
• BigQuery works with Google Cloud Storage From the official documentation: “Load Cloud Storage data into BigQuery”
• Cloud Storage works with Dataflow From the official documentation: “Write from Dataflow to Cloud Storage”
• Cloud Storage works with Sensitive Data Protection From the official documentation: “Uses the Data Loss Prevention API to analyze a file on GCS.”
• BigQuery works with Pub/Sub From the official documentation: “createBigQuerySubscription creates a Pub/Sub subscription that exports messages to BigQuery.”
• 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.”
• 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.”
• Data Catalog is part of Knowledge Catalog From the official documentation: “Knowledge Catalog features”
• BigQuery works with Data Catalog From the official documentation: “The instructions in this page use both BigQuery and Data Catalog.”
• 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 depends on Cloud Storage From the official documentation: “Begin by creating a Cloud Storage bucket using the Google Cloud console or Google Cloud CLI. The Dataflow pipeline uses this bucket as a temporary storage location.”
• Dataflow depends on Google Cloud Storage From the official documentation: “- A gcs bucket for staging DataFlow files. Replace `<BUCKET_NAME>`: the name of a valid Google Cloud Storage bucket.”
• Dataflow works with Google Cloud Storage From the official documentation: “Data is transferred between Spanner and Cloud Storage using Dataflow.”
• 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.”
• VPC Service Controls secures Google Cloud Storage From the official documentation: “Storage Transfer Service supports on-premises transfers to Cloud Storage buckets protected by VPC Service Controls, under the following conditions:”
• VPC Service Controls secures Knowledge Catalog From the official documentation: “The API for Knowledge Catalog can be protected by VPC Service Controls and the product can be used normally inside service perimeters.”
• BigQuery depends on Cloud Storage From the official documentation: “BigQuery relies on Cloud Storage for staging file data and supports reading from and writing to several other sources and Google Cloud services.”
• BigQuery is an alternative to Dataflow From the official documentation: “To automate the EDA process, use BigQuery or a managed data processing service like Dataflow.”
• BigQuery works with VPC Service Controls From the official documentation: “BigQuery integrates with VPC Service Controls to restrict access to your BigQuery resources from specific networks.”
• Cloud Storage works with Data Catalog From the official documentation: “Data Catalog supports the definition of Cloud Storage file entries and their schema.”
• Cloud Storage works with Knowledge Catalog From the official documentation: “To automatically discover and build inventories of the data assets, integrate Knowledge Catalog with your storage systems, such as [BigQuery](/bigquery/docs/introduction), [Cloud Storage](/storage/docs/introduction), and [Pub/Sub](/pubsub/docs/overview).”
• Data Catalog works with Pub/Sub From the official documentation: “Pub/Sub topics are automatically registered with the Data Catalog.”
• Data Catalog works with VPC Service Controls From the official documentation: “The Data Catalog integration with VPC Service Controls has no known limitations.”
• Dataflow works with VPC Service Controls From the official documentation: “To customize DNS resolution when using Dataflow with VPC Service Controls, use Cloud DNS [private zones](/dns/docs/overview#dns-private-zones) instead of using custom BIND servers.”
• dynamic data masking is part of BigQuery From the official documentation: “BigQuery supports [dynamic data masking](/bigquery/docs/column-data-masking-intro) at the column level.”
• dynamic data masking depends on Data Catalog From the official documentation: “The Data Catalog API (`datacatalog.googleapis.com`) must remain enabled in projects that use BigQuery column-level access control or dynamic data masking.”
• Google Cloud Storage works with Pub/Sub From the official documentation: “Both Google Managed Service for Apache Kafka and Pub/Sub integrates with various Google Cloud services like Dataflow, BigQuery, Cloud Storage, and more.”
• Google 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.”
• Google Cloud Storage works with Sensitive Data Protection From the official documentation: “This page describes how Sensitive Data Protection can create de-identified copies of data stored in Cloud Storage.”
• Knowledge Catalog depends on Cloud Storage From the official documentation: “Looker (Google Cloud core) publishes LookML metadata to regional Cloud Storage repositories for Knowledge Catalog to consume through a batch sync process.”
• Knowledge Catalog works with Pub/Sub From the official documentation: “To automatically discover and build inventories of the data assets, integrate Knowledge Catalog with your storage systems, such as [BigQuery](/bigquery/docs/introduction), [Cloud Storage](/storage/docs/introduction), and [Pub/Sub](/pubsub/docs/overview).”
• Knowledge Catalog works with VPC Service Controls From the official documentation: “The integration between Looker (Google Cloud core) and Knowledge Catalog supports VPC Service Controls.”
• 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.”
• VPC Service Controls secures Dataflow From the official documentation: “Place your Dataflow pipelines inside a security perimeter using VPC Service Controls.”
• 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.”