Build and operate the data processing systems behind analytics and ML on Google Cloud, including BigQuery, Dataflow, and Pub/Sub, and track your readiness for the Professional Data Engineer exam.
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Google Cloud service
Looker
Topic in 5 exam domains
Also called: enterprise Looker, Google Cloud Looker, Looker Platform
A business intelligence and data analytics platform that can host extensions.
Where this appears on the exam
4 objectives in 2 of 5 domains
Related topics
This topicWorks alongsideBuilds on theseBuilds on theseAppliedcustomer-managed encryption keysFeature
LookerService
Data StudioServiceLooker Action HubServiceAlloyDB for PostgreSQLServiceAmazon S3ServiceSensitive Data ProtectionServiceCloud RunServiceGoogle Cloud StorageServiceExploreConceptCloud StorageServiceLookConceptCloud LoggingServiceCompute EngineServiceLookMLFeatureGoogle SecOpsServiceBigQueryServiceCloud SQLServiceBigQuery BI EngineServicePoints to what builds on itWorks with or alternative toHover or tap a line to see what connects the two
- BigQuery works with Looker From the official documentation: “Connect Looker to the BigQuery project.”
- Cloud SQL works with Looker From the official documentation: “To get started, see [Use Looker with Cloud SQL](/sql/docs/sqlserver/looker).”
- Explore is part of Looker From the official documentation: “Ex = [Explore](/looker/docs/creating-and-editing-explores)”
- Look is part of Looker From the official documentation: “In Looker, a [Look](/looker/docs/saving-and-editing-looks) is a single query that was previously saved.”
- Looker works with Looker Action Hub From the official documentation: “To use Looker integrations, the Looker Action Hub and the Looker instance must be able to communicate with one another.”
- LookML is part of Looker From the official documentation: “- `get_models`: List all LookML models on your Looker instance.”
- AlloyDB for PostgreSQL works with Looker From the official documentation: “Looker supports connections to [AlloyDB for PostgreSQL](/alloydb/docs/overview), a fully managed, cloud-native database service from Google Cloud that is compatible with PostgreSQL.”
- Amazon S3 works with Looker From the official documentation: “Amazon S3 buckets are a common way to store large amounts of data. You or your company will need to have created an S3 bucket with Amazon before Looker can use it.”
- 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.”
- customer-managed encryption keys works with Looker From the official documentation: “CMEK is supported only for Looker data sources.”
- 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).”
- Google SecOps works with Looker From the official documentation: “View both predefined Google SecOps SOAR reports and advanced reports using<br>Looker”
- 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 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”
- Cloud Storage works with Google SecOps From the official documentation: “Configure a feed in Google SecOps to ingest from Google Cloud Storage”
- 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).”
- Cloud Run works with Cloud SQL From the official documentation: “Learn how to connect to Cloud SQL from Cloud Run”
- Amazon S3 works with Google SecOps From the official documentation: “Configure AWS S3 bucket and IAM for Google SecOps”
- Cloud Logging works with customer-managed encryption keys From the official documentation: “To use Cloud Logging with Customer-managed encryption keys (CMEK), you must complete the steps in the [Enable CMEK for an organization](/logging/docs/routing/managed-encryption#enable) page in the Cloud Logging documentation.”
- Cloud SQL works with Cloud Storage From the official documentation: “When ingesting data from Cloud SQL, data is first staged to a Cloud Storage bucket.”
- Cloud SQL works with Compute Engine From the official documentation: “Create a Compute Engine VM Instance to host a sample web app that connects to Cloud SQL.”
- Cloud Run works with Cloud Storage From the official documentation: “Route Cloud Storage events to Cloud Run”
- Google Cloud Storage works with Google SecOps From the official documentation: “Google SecOps uses a unique service account to read data from your GCS bucket.”
- 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 Storage works with Sensitive Data Protection From the official documentation: “Uses the Data Loss Prevention API to analyze a file on GCS.”
- customer-managed encryption keys secures Cloud Storage From the official documentation: “CMEKs encrypt data at rest in Cloud SQL, Cloud Storage, and within GKE clusters.”
- Cloud Logging works with Cloud SQL From the official documentation: “Cloud SQL uses Cloud Logging.”
- Cloud SQL depends on Compute Engine From the official documentation: “Cloud SQL uses Compute Engine virtual machines (VMs) with persistent storage disks.”
- customer-managed encryption keys secures BigQuery From the official documentation: “You can either create CMEKs manually to protect your BigQuery resources or use Cloud KMS Autokey.”
- customer-managed encryption keys secures Cloud SQL From the official documentation: “Enable CMEK for Cloud SQL Databases”
- Cloud Storage works with customer-managed encryption keys From the official documentation: “Cloud Storage supports CMEK for routing logs.”
- Amazon S3 is an alternative to Cloud Storage From the official documentation: “Data must be stored in either a Cloud Storage or Amazon S3 bucket.”
- 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 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.”
- AlloyDB for PostgreSQL works with BigQuery From the official documentation: “BigQuery AlloyDB federation lets BigQuery query data residing in AlloyDB in real time without copying or moving the data.”
- AlloyDB for PostgreSQL works with Cloud Storage From the official documentation: “AlloyDB supports importing and exporting compressed `.gz` files from Cloud Storage.”
- BigQuery depends on Cloud Logging From the official documentation: “BigQuery utilizes Cloud Logging for some of your log data.”
- BigQuery works with Google SecOps From the official documentation: “Google SecOps exports the following categories of data to your BigQuery project:”
- Cloud Logging works with Compute Engine From the official documentation: “Compute Engine sends you Cloud Logging events for scheduled, started, or completed maintenance.”
- Cloud Run works with Google Cloud Storage From the official documentation: “The Cloud Run function will receive syslog messages from FortiEDR via HTTP and write them to GCS.”
- 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.”
- Cloud Storage works with Compute Engine From the official documentation: “You can use a web browser, the Google Cloud CLI, or a programming language to transfer files between Cloud Storage and Compute Engine VMs.”
- Compute Engine works with Google Cloud Storage From the official documentation: “The usage export bucket is a Google Cloud Storage bucket where Compute Engine usage reports are stored.”
- AlloyDB for PostgreSQL works with Cloud Run From the official documentation: “The Cloud Run service can connect to the AlloyDB instance.”
- AlloyDB for PostgreSQL is an alternative to Cloud SQL From the official documentation: “The sample code uses Cloud SQL as the vector database, whereas this reference architecture uses AlloyDB for PostgreSQL.”
- 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 works with Cloud Run From the official documentation: “You can then use Cloud Run to transcode data present in the bucket and move it to BigQuery.”
- BigQuery BI Engine is part of BigQuery From the official documentation: “BI Engine acceleration is part of BigQuery job processing.”
- Cloud Logging works with Cloud Run From the official documentation: “Cloud Logging captures, stores, and analyzes Cloud Run logs.”
- 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.”
- Cloud Logging works with Google SecOps From the official documentation: “This document explains how to integrate Cloud Logging with Google Security Operations.”
- customer-managed encryption keys secures Cloud Logging From the official documentation: “Cloud Logging supports encrypting Log storage with CMEK keys.”
- customer-managed encryption keys is part of Cloud Storage From the official documentation: “[Cloud Storage](/storage/docs/introduction) provides features such as customer-managed encryption, lifecycle management, and aging and retention policies.”
- customer-managed encryption keys secures Compute Engine From the official documentation: “In IL5, CMEK is enabled by default for Compute Engine, Google Kubernetes Engine (GKE), Cloud Storage, and Cloud SQL.”
- Google SecOps depends on Cloud Storage From the official documentation: “Google SecOps uses a unique service account to read data from your GCS bucket.”
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