Company
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October 9, 2024

USAA Backs Bigeye with $5M Investment

This investment underscores USAA’s confidence in Bigeye's vision to enhance data quality and reliability.

Adrianna Vidal

At Bigeye, our mission is simple: to ensure enterprises have reliable, high-quality data that supports critical business decisions. Today, we’re excited to share that USAA, a current Bigeye customer and one of the most trusted names in financial services, has made a strategic $5 million investment in Bigeye.

A Partnership Built on Trust and Impact

USAA has been a valued customer of Bigeye, working closely with us to drive improvements in managing data quality across their organization. As an enterprise with over 37,000 employees and 13 million members, USAA relies on accurate and trusted analytics to make key business decisions. Their teams have been leveraging Bigeye’s platform to proactively monitor and resolve data issues, ensuring the high standards needed to effectively serve their members.

USAA’s decision to invest in Bigeye was a natural next step in our collaboration. Nathan McKinley, Vice President and Head of Corporate Development at USAA, shared his thoughts on the partnership: “As a Bigeye customer, we quickly recognized the value their platform brings to enhancing data quality and reliability across enterprise organizations. Our decision to invest in Bigeye was driven by our experience with the company and our belief that similar enterprise organizations will be accelerating their adoption of data observability tools.”

Powering USAA’s Data Strategy

For an organization of USAA’s size and scale, data quality management is crucial. With Bigeye, USAA has streamlined its data quality management, enabling teams to proactively monitor and resolve data issues in real-time. This has empowered their teams to stay ahead of potential issues, simplifying the process of maintaining data integrity across their operations.

Tina Cragg, Head of Enterprise Information and Insights at USAA, noted the impact: "Managing data quality across our complex data landscape is a continuous challenge, but Bigeye has been a great partner to us and provided the tools and insights needed to stay ahead. Their platform allows us to monitor data health in real-time, ensuring that we meet the high standards required to serve our members effectively."

A Milestone for Bigeye

This investment also marks a significant milestone for Bigeye, bringing our total fundraising to $73.5 million. It further strengthens our commitment to delivering enterprise-grade solutions that simplify and enhance data quality management for the largest organizations.

Kyle Kirwan, Bigeye CEO and Founder, reflected on the collaboration: “We are proud to support USAA’s mission to serve the military community. Managing data quality at USAA’s scale is no small task, and our partnership empowers their teams to proactively monitor and resolve data issues within their existing workflows. This collaboration not only highlights the critical role of data observability in large-scale environments but also reinforces Bigeye’s position as the leader in enterprise-grade solutions that make data trustworthy by default.”

Looking Ahead

With USAA’s investment, we’re excited to continue growing our platform and delivering the best possible data observability solutions to enterprises.

Interested in seeing how Bigeye can simplify data observability for your organization? Request a personalized demo today or try our online interactive demo. And if you want to hear more about how other enterprises are benefiting from Bigeye, explore our customer stories for real-world insights.

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Resource
Monthly cost ($)
Number of resources
Time (months)
Total cost ($)
Software/Data engineer
$15,000
3
12
$540,000
Data analyst
$12,000
2
6
$144,000
Business analyst
$10,000
1
3
$30,000
Data/product manager
$20,000
2
6
$240,000
Total cost
$954,000
Role
Goals
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
Monitoring
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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