Introduction to analysis and business intelligence tools

You can integrate analysis and business intelligence (BI) tools with BigQuery to discover actionable insights from your data warehouse. Several tools complement BigQuery, letting you build interactive dashboards, create custom data applications, or perform programmatic analysis without moving your datasets.

Connected Sheets

Connected Sheets lets you access, analyze, visualize, and share billions of rows of BigQuery data from your Google Sheets spreadsheets. The Connected Sheets interface simplifies collaboration with non-technical project stakeholders, requires no additional data exports, streamlines reporting, and provides powerful access control capabilities.

To learn more about using Connected Sheets with BigQuery, see Use Connected Sheets.

Looker

Looker is Google's enterprise platform for data visualization and business intelligence. It is useful for advanced data analytics, predictive analysis, and custom data applications. It can also connect to transactional databases in other public clouds.

To learn more about using Looker with BigQuery, see Analyze data with BigQuery BI Engine and Looker.

Data Studio

Data Studio is a Google tool for data visualization and business intelligence. It connects to BigQuery directly from the Google Cloud console and is useful for building graphics, reports, and dashboards.

To learn more about using Data Studio with BigQuery, see Analyze data with Data Studio.

Programmatic analysis tools

Programmatic analysis tools can run code to analyze data managed in BigQuery. While SQL is a powerful query language, Python, Java, or R often provide a more simplified, expressive way to perform data analysis. Such tools include open source web-based applications like Jupyter Notebooks and Apache Zeppelin. Vertex AI Workbench is a Google tool that offers JupyterLab notebook environments for programmatic analysis.

Third-party tools

You can also connect to BigQuery using a number of popular third-party tools such as Tableau and Microsoft Power BI.

The BigQuery Ready program offers a full list of validated partner solutions.

If you need assistance with a solution, consider contacting a Google Cloud Ready - BigQuery partner. Third-party software isn't supported by Cloud Customer Care when it has been identified that BigQuery is working as intended.

Network connectivity

All BI and data analytics solutions that are deployed on hosts and services with external IP addresses can access BigQuery through the public BigQuery REST API and the RPC-based BigQuery Storage API over the internet.

Third-party BI and data analytics solutions that are deployed on Compute Engine VM instances that only have internal IP addresses can use Private Google Access to reach Google APIs and services like BigQuery. To enable a subnet for Private Google Access and view the requirements, see Configuring Private Google Access.

Third-party BI and data analytics solutions that are deployed on on-premises hosts can use Private Google Access for on-premises hosts to reach Google APIs and services like BigQuery. This service establishes a private connection over a Cloud VPN or Cloud Interconnect from your data center to Google Cloud. On-premises hosts don't need external IP addresses; instead, they use internal RFC 1918 IP addresses. To enable Private Google Access for on-premises hosts, you must configure DNS, firewall rules, and routes in your on-premises and VPC networks. For more details on Private Google Access for on-premises hosts, see Configuring Private Google Access for on-premises hosts.

If you manage your own instance of a third-party BI solution, consider deploying it on Compute Engine to minimize latency between your instance and BigQuery.

If your BI solution supports it, you might consider setting filters in report or dashboard queries whenever possible. This step pushes the filters as WHERE clauses to BigQuery. Although setting these filters doesn't reduce the amount of data that BigQuery scans, it does reduce the amount of data that comes back over the network.

For more information on network and query optimizations, see Optimize workloads and the Introduction to optimizing query performance.

ODBC and JDBC drivers

For third-party solutions and custom applications that don't integrate with the BigQuery API, Magnitude Simba provides ODBC and JDBC drivers to help you use BigQuery with your existing tools.

Authentication

The BigQuery API uses OAuth 2.0 access tokens to authenticate requests. An OAuth 2.0 access token is a string that grants temporary access to an API. Google's OAuth 2.0 server grants access tokens for all Google APIs. Access tokens are associated with a scope, which limits the token's access. For scopes associated with the BigQuery API, see the complete list of Google API scopes.

Solutions that offer native BigQuery integration can automatically generate access tokens for BigQuery by using OAuth 2.0 protocols or customer-supplied service account private keys. Similarly, solutions that rely on Simba ODBC/JDBC drivers can also obtain access tokens for a Google user account or for a Google service account.

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