BigQuery
Integrate and automate enterprise data processes. BigQuery can handle massive datasets and scales seamlessly to accommodate growing data needs without complex infrastructure management.
Build BigQuery data into your business processes
Achieve consistent data management.
Enhance data integrity
Process the right data at the right time and get it to the right place.
Handle complexity
Manage data and database dependencies in key processes.
Deliver data on time
Automate job sequencing based on data readiness.
Meticulous process execution
Google BigQuery is a powerful serverless, multi-cloud data warehouse that enables enterprise data analysis. Running queries and generating reports or datasets are important steps in data analytics processes. Google BigQuery only offers basic capabilities for on-demand or batch queries, and scheduled queries require coding in standard SQL.
With the Tidal adapter for Google BigQuery, you can apply more advanced scheduling capabilities to your queries and results – no coding or scripting required. Integrate your Google BigQuery data with other enterprise data and locations for precise sequencing and synchronization of tasks to execute processes with timely, accurate results
What the adapter enables
Through the integration, you can use jobs in Tidal to:
- Automate delivery of data to the right place at the right time – manipulate, copy and move it across systems
- Orchestrate multi-cloud data analysis
- Perform interactive data analysis with the Google BigQuery BI engine
- Run BigQuery machine learning models on your data
- Run queries and generate results, and use those events to trigger other activities in your schedule
Comprehensive logging in Tidal enables you to satisfy audit and regulatory requirements with controls for tracking what happens with data and who makes changes
How it works
The Tidal adapter enhances Google BigQuery scheduling with advanced features like time/event-based triggers, dependencies and calendar support, all managed centrally without coding. This enables seamless integration of BigQuery data with other enterprise systems for precise task sequencing and synchronization.
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What will an automation fabric do for your organization?
Establish frictionless orchestration with Tidal.
Tidal and Google BigQuery integration FAQs
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What is Google BigQuery used for?
BigQuery is Google Cloud Platform's serverless data warehouse designed for large-scale data storage and analysis. It enables fast queries on petabytes of data using SQL and offers AI/ML capabilities.
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What is a BigQuery integration?
The Tidal adapter for BigQuery connects various data sources and applications to Google BigQuery, a serverless, petabyte-scale data warehouse for efficient data storage, analysis and insights using SQL-like queries.
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Does BigQuery have an API?
Yes. The BigQuery API allows programmatic interaction with BigQuery, enabling tasks like managing datasets, tables, jobs and routines and data ingestion and querying. It offers REST and gRPC APIs and supports client libraries in various languages.
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How do I connect to Google BigQuery?
The Tidal adapter for Google Cloud BigQuery is part of a standard Tidal installation. When the installation is complete, you can create a Google Cloud BigQuery connection. License and configure the adapter before running Google Cloud BigQuery jobs.
To connect a Tidal adapter to BigQuery, you will need to:
Authenticate with BigQuery:
- Project ID: The unique identifier of your BigQuery project
- Service Account Key: A JSON file containing the credentials for a service account with the necessary permissions to access your BigQuery data
Configure the connection in Tidal:
- Access the connection settings: In Tidal, navigate to the data source or connector configuration area.
- Enter credentials: Input the Project ID and upload the service account key file.
- Test the connection: Verify that Tidal can successfully connect to BigQuery by testing the connection.