January 11, 2023

Bigeye is now on the Google Cloud Marketplace

We are thrilled to announce that Bigeye is now available on the Google Cloud Platform (GCP) Marketplace.

Kyle Kirwan

We are thrilled to announce that Bigeye is now available on the Google Cloud Platform (GCP) Marketplace!

With Bigeye, your team gets better data quality, at any scale. Companies ranging from small startups to enterprises trust Bigeye to securely raise the bar on data quality, whether they have hundreds or billions of data points.

Now, Google Cloud users can get started immediately through our Marketplace offering. Purchase a Bigeye SaaS subscription directly on the marketplace today. Or contact Bigeye for custom environment sizing.

The GCP Marketplace houses software for users to research and deploy. If you join the GCP Marketplace, you’ll be able to enjoy many benefits like: consolidated Google Cloud billing, faster procurement (skip the approvals!), and quicker time to ROI.

Want to learn more? Here are some FAQs for Bigeye users:


Q: Which plans and pricing are available on GCP Marketplace?

A: You can purchase a subscription to Bigeye directly on marketplace, no contact to us, for $50k for 200 tables.

Q: Do I need a GCP marketplace account for this?

A: Yes. To proceed, your project must be enabled for purchase by your billing administrator.

Q: Where will I see how much I’m being charged for Bigeye?

A: All billing through marketplaces will be charged through your cloud provider. Check the billing console from your cloud provider.

Q: If I’m already a Bigeye customer, how do I switch to billing on the GCP marketplace?

A: Subscribing to GCP marketplace will automatically create a new organization for you. If you want to use GCP billing for an existing project, please reach out to and we’ll help you with details and migration.

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Software/Data engineer
Data analyst
Business analyst
Data/product manager
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Common needs
Data engineers
Overall data flow. Data is fresh and operating at full volume. Jobs are always running, so data outages don't impact downstream systems.
Freshness + volume
Schema change detection
Lineage monitoring
Data scientists
Specific datasets in great detail. Looking for outliers, duplication, and other—sometimes subtle—issues that could affect their analysis or machine learning models.
Freshness monitoringCompleteness monitoringDuplicate detectionOutlier detectionDistribution shift detectionDimensional slicing and dicing
Analytics engineers
Rapidly testing the changes they’re making within the data model. Move fast and not break things—without spending hours writing tons of pipeline tests.
Lineage monitoringETL blue/green testing
Business intelligence analysts
The business impact of data. Understand where they should spend their time digging in, and when they have a red herring caused by a data pipeline problem.
Integration with analytics toolsAnomaly detectionCustom business metricsDimensional slicing and dicing
Other stakeholders
Data reliability. Customers and stakeholders don’t want data issues to bog them down, delay deadlines, or provide inaccurate information.
Integration with analytics toolsReporting and insights

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