BigQuery Overview Google Professional Data Engineer GCP

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  2. BigQuery Overview Google Professional Data Engineer GCP
  • fully managed, petabyte scale, low cost analytics data warehouse.
  • It is NoOps—no infrastructure to manage
  • Functions to be done on BigQuery
    • Loading and exporting data
    • Querying and viewing data
    • Managing data
  • Access by
    • The BigQuery web UI in the Cloud Console
    • The BigQuery classic web UI
    • The BigQuery command-line tool
    • The BigQuery REST API or client libraries

Cost Control

For cost control costs

  • Estimate cost of a query before execution
  • Estimate storage costs
  • Set custom cost controls using custom quotas
  • Analyze audit logs to monitor query costs and BigQuery usage


Access Control

  • Access control by Cloud Identity and Access Management
  • For access to BigQuery resource, assign roles to a user, group, or service account.
  • If roles given at organization and project level, then can run BigQuery jobs or manage all of a project’s BigQuery resources.
  • Roles at the dataset level provide access only to one or more datasets.
  • Datasets are child resources of projects.
  • Tables and views are child resources of datasets —inherit permissions from their parent dataset.
  • It automatically encrypts all data before it is written to disk.
  • Also automatically decrypted when read by an authorized user.
  • By default, Google manages the key encryption keys used to protect data.
  • Option to use customer-managed encryption keys