datasets

Related topics

• Dataflow works with datasets From the official documentation: “BigQuery uses datasets to contain the data that it receives from Dataflow.”
• datasets is part of BigQuery From the official documentation: “To organize and control access to data in BigQuery, you provision top-level containers called [datasets](/bigquery/docs/datasets-intro).”
• 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: “Sample to load Avro data from Cloud Storage into a new BigQuery table”
• BigQuery works with Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• BigQuery works with Sensitive Data Protection From the official documentation: “Uses the Data Loss Prevention API to analyze BigQuery data.”
• Dataflow works with Pub/Sub From the official documentation: “Pub/Sub notifies Dataflow about the upload.”
• BigQuery works with Dataflow From the official documentation: “Read from BigQuery to Dataflow”
• Dataflow works with Spanner From the official documentation: “Use Dataflow to load data into Spanner.”
• Cloud Storage works with Dataflow From the official documentation: “Write from Dataflow to Cloud Storage”
• Pub/Sub works with Sensitive Data Protection From the official documentation: “Inspect Datastore, using Pub/Sub for job status notifications.”
• 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 works with Spanner From the official documentation: “Federated analytics seamlessly combine data from Spanner and other sources in BigQuery.”
• 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 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 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 Logging works with Cloud Storage From the official documentation: “Cloud Storage writes various log entries to Cloud Logging in the Google Cloud console.”
• Cloud Storage works with Pub/Sub From the official documentation: “| **Google Cloud** | Cloud Storage | Pub/Sub |”
• BigQuery works with Google Cloud Storage From the official documentation: “Load Cloud Storage data into 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.”
• 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.”
• BigQuery depends on Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
• Cloud Logging is an alternative to Cloud Storage From the official documentation: “Instead, they are routed to either Cloud Storage (recommended) or Cloud Logging, depending on your organization's configuration.”
• Cloud Logging works with Google Cloud Storage From the official documentation: “Cloud Logging can [route logs](/logging/docs/export/configure_export_v2) to Cloud Storage by Google SecOps on a scheduled basis.”
• Cloud Logging is an alternative to Google Cloud Storage From the official documentation: “When you specify your own service account for builds, you must store your build logs in a Cloud Logging bucket, in a user-created Cloud Storage bucket, or in a Google Cloud-created and user-owned Cloud Storage bucket.”
• Dataflow works with Google Cloud Storage From the official documentation: “When you run a pipeline using Dataflow, your results are stored in a Cloud Storage bucket.”
• Dataflow works with Sensitive Data Protection From the official documentation: “This proof-of-concept uses Dataflow and Sensitive Data Protection to securely tokenize and import data from a relational database to BigQuery.”
• Google Cloud Storage works with Spanner From the official documentation: “- Export any Spanner database into a Cloud Storage bucket using either Avro or CSV file formats.”
• 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.”
• Cloud Logging works with Dataflow From the official documentation: “You can control the volume of Dataflow logs ingested by Cloud Logging by following the [Filter logs documentation](/dataflow/docs/guides/filter-logs).”
• Cloud Logging works with Spanner From the official documentation: “Both Spanner and Agent Platform provide monitoring dashboards and write logs to Cloud Logging, which can contain additional details.”
• Cloud Storage works with Spanner From the official documentation: “Move Spanner databases to and from Avro or CSV files stored in Cloud Storage.”
• 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.”
• 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.”