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Google Cloud service
BigQuery BI Engine
Topic in 6 exam domains
- BigQuery BI Engine · Service · Google Cloud
- BigQuery BI Engine · Feature · BigQuery feature
Also called: BI Engine, bigquerybiengine
An analysis acceleration service integrated with BigQuery that accelerates SQL queries.
Where this appears on the exam
5 objectives in 2 of 5 domains
~22% of exam
~15% of exam
Related topics
FoundationsBuilding blocksThis topicWorks alongsideAppliedCloud SQLServiceSensitive Data ProtectionServiceGoogle Cloud StorageServiceBigQueryServiceBigQuery APIService
BigQuery BI EngineService
Cloud MonitoringServicedata maskingFeatureData StudioServiceLookerServiceBigQuery Data Transfer ServiceServiceManaged Service for Apache AirflowServiceApigeeServiceBI Engine reservationsFeaturePoints to what builds on itWorks with or alternative toHover or tap a line to see what connects the two
- BigQuery works with BigQuery BI Engine From the official documentation: “BigQuery BI Engine lets you perform fast, low-latency analysis services and interactive analytics with reports and dashboards backed by BigQuery.”
- BigQuery BI Engine is part of BigQuery From the official documentation: “BI Engine acceleration is part of BigQuery job processing.”
- BI Engine reservations is part of BigQuery BI Engine From the official documentation: “If you choose to create BI Engine reservations to improve the performance of your dashboards, you incur costs for the reservation you create in BI Engine.”
- BigQuery API works with BigQuery BI Engine From the official documentation: “BI Engine directly integrates with the BigQuery API.”
- BigQuery BI Engine works with Cloud Monitoring From the official documentation: “You can monitor and configure alerts for BigQuery BI Engine with Cloud Monitoring.”
- BigQuery BI Engine works with data masking From the official documentation: “Compatible. Data masking policies are enforced in the BI Engine.”
- BigQuery BI Engine works with Data Studio From the official documentation: “BI Engine integrates with Data Studio to accelerate data exploration and analysis.”
- BigQuery BI Engine works with Looker From the official documentation: “If you are using [BigQuery BI Engine](/bigquery/docs/bi-engine-intro) with Looker, you can use the **Query Performance Metrics** Explore to view database-specific information about your queries.”
- BigQuery works with Sensitive Data Protection From the official documentation: “Uses the Data Loss Prevention API to analyze BigQuery data.”
- BigQuery works with BigQuery Data Transfer Service From the official documentation: “The BigQuery Data Transfer Service uses load jobs to load Amazon S3 data into BigQuery.”
- BigQuery works with Cloud SQL From the official documentation: “Add credentials to connect BigQuery to Cloud SQL.”
- BigQuery works with Data Studio From the official documentation: “Select the BigQuery [connector](/data-studio/connector).”
- BigQuery works with Looker From the official documentation: “Connect Looker to the BigQuery project.”
- BigQuery works with Cloud Monitoring From the official documentation: “You can use Monitoring to export your metrics to BigQuery.”
- 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 Google Cloud Storage From the official documentation: “Load Cloud Storage data into BigQuery”
- Cloud Monitoring works with Cloud SQL From the official documentation: “You can also get more details by viewing the Cloud Monitoring logs for your Cloud SQL destination instance.”
- 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 SQL works with Looker From the official documentation: “To get started, see [Use Looker with Cloud SQL](/sql/docs/sqlserver/looker).”
- Cloud SQL works with Sensitive Data Protection From the official documentation: “Sensitive Data Protection starts identifying your Cloud SQL instances and creating a default connection for each instance.”
- Managed Service for Apache Airflow depends on Cloud SQL From the official documentation: “Managed Airflow uses Cloud SQL to run Airflow database.”
- Cloud SQL works with Google Cloud Storage From the official documentation: “Imports data into a Cloud SQL instance from a SQL dump or CSV file in Cloud Storage.”
- Managed Service for Apache Airflow depends on Google Cloud Storage From the official documentation: “Managed Airflow uses a [Cloud Storage](/storage) bucket to store DAGs of your Managed Airflow environment.”
- Apigee works with BigQuery From the official documentation: “You can use the Apigee API to export all analytics data for an entire day from Apigee to your own data repository, such as Google Cloud Storage or BigQuery.”
- Apigee depends on BigQuery API From the official documentation: “Apigee uses the BigQuery API to leverage BigQuery export features when exporting to Cloud Storage.”
- Apigee works with Cloud Monitoring From the official documentation: “If you are behind a corporate proxy or firewall, Apigee may not be able to send metrics to Cloud Monitoring with its default settings.”
- Apigee works with Data Studio From the official documentation: “A Data Studio data source can connect to a single Apigee organization.”
- Apigee works with Google Cloud Storage From the official documentation: “You can use the Apigee API to export all analytics data for an entire day from Apigee to your own data repository, such as Google Cloud Storage or BigQuery.”
- BI Engine reservations works with Data Studio From the official documentation: “[BI Engine reservations](/bigquery/docs/bi-engine-intro) can improve the performance of Data Studio dashboards.”
- BigQuery API is part of BigQuery From the official documentation: “BigQuery, including the BigQuery API and the target table.”
- BigQuery Data Transfer Service depends on BigQuery API From the official documentation: “Create a project and enable the BigQuery API.”
- BigQuery Data Transfer Service works with Cloud Monitoring From the official documentation: “The BigQuery Data Transfer Service exports logs and metrics to Cloud Monitoring and Cloud Logging that provide observability into your transfers.”
- BigQuery Data Transfer Service works with Cloud SQL From the official documentation: “To transfer data from a private Cloud SQL instance in one project to BigQuery in another project, BigQuery Data Transfer Service requires a connector network to bridge private network connectivity.”
- BigQuery Data Transfer Service works with Google Cloud Storage From the official documentation: “As part of the data transfer, BigQuery Data Transfer Service writes data from Amazon Redshift to Cloud Storage as CSV files.”
- Cloud Monitoring works with Google Cloud Storage From the official documentation: “You can configure Cloud Storage client libraries to to generate gRPC related metrics in Cloud Monitoring.”
- 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.”
- Cloud SQL works with Data Studio From the official documentation: “Data Studio supports both public and private IP connections to PostgreSQL on Cloud SQL.”
- Cloud SQL works with Managed Service for Apache Airflow From the official documentation: “Managed Airflow updates the Airflow `airflow_db` connection to point to the new Cloud SQL database.”
- Data Studio works with Google Cloud Storage From the official documentation: “All the data you upload via Data Studio is stored in Google Cloud Storage.”
- Data Studio works with Looker From the official documentation: “See the [Connecting to Data Studio](/looker/docs/looker-studio-connector) documentation page to learn more about connecting Looker and Data Studio.”
- Data Studio is an alternative to Looker From the official documentation: “You can also [export these recommendations to BigQuery](/recommender/docs/bq-export/export-recommendations-to-bq) and then examine them using [Data Studio](/bigquery/docs/visualize-looker-studio) or [Looker](/bigquery/docs/looker).”
- Data Studio works with Sensitive Data Protection From the official documentation: “After calculating [*k*-anonymity](/sensitive-data-protection/docs/concepts-risk-analysis#about-k-anonymity) values for a dataset using Sensitive Data Protection, you can visualize the results in Data Studio.”
- Google Cloud Storage works with Managed Service for Apache Airflow From the official documentation: “When you create an environment, Managed Airflow creates a [Cloud Storage](/storage) bucket and associates the bucket with your environment.”
- 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.”
- Managed Service for Apache Airflow depends on BigQuery From the official documentation: “This happens because Google Kubernetes Engine depends on BigQuery and Managed Service for Apache Airflow inherits this dependency from the Kubernetes Engine API.”
- Managed Service for Apache Airflow depends on BigQuery API From the official documentation: “**Important:** If you disable the BigQuery API, your Managed Airflow environment stops working. This happens because Google Kubernetes Engine depends on BigQuery and Managed Service for Apache Airflow inherits this dependency from the Kubernetes Engine API.”
- 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.”
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