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January 8, 2025

Achieving Data Transparency at Scale: Freedom Mortgage’s Success with Bigeye

We spoke with Eric Chesebro, executive vice president of data governance at Freedom Mortgage, to discuss how they’ve transformed their data governance strategy using Bigeye.

Adrianna Vidal
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Freedom Mortgage, a top-five mortgage originator and servicer, handles massive volumes of data daily. With a mission to provide homeownership opportunities across the country, Freedom Mortgage constantly manages critical data to deliver efficient, reliable services to its homeowners. However, large amounts of data present even larger challenges—especially when it comes to governing that data at scale.

We spoke with Eric Chesebro, executive vice president of data governance at Freedom Mortgage, to discuss how they’ve transformed their data governance strategy and partnered with Bigeye to solve the challenges of managing data at scale.

The Data-Driven Heart of Freedom Mortgage

Mortgage servicing and origination at Freedom Mortgage are deeply dependent on managing vast amounts of sensitive data: “The mortgage transaction itself is purely fed by data,” said Eric. “There is no other consumer transaction that collects more data on an individual than a mortgage transaction.” 

From a prospective homeowner’s application to their final monthly payments, every step of the process requires precision in how that data is collected, processed, and monitored: “At its heart, Freedom Mortgage is a data company,” Eric emphasized.

With this in mind, ensuring that all of this data is managed accurately and transparently is essential for providing reliable service to more than two million customers in the United States.

The Challenge: Managing Data at Scale

The challenge Freedom Mortgage faced was how to manage its vast data with limited resources: “We’re a small team,” Eric explained. “The problem was: How do we govern at scale?”

Picture a flood of information flowing into their systems—loan applications, servicing data, customer details—each one critical and sensitive: “There’s a tremendous amount of data that comes in at the top of the funnel,” Eric said. 

Akin to the narrowing funnel, only a small portion of this data was effectively governed at the bottom. The team, focused on the most critical assets, left some of the data at the top, unmonitored, creating gaps in visibility.

“How do we govern more of that data? How do we put oversight and monitoring at the top of the funnel so that we have transparency on all the data coming in?”

Without this visibility, maintaining consistency and transparency across their growing data landscape became increasingly difficult.

The Solution: Bigeye and Data Observability

That’s when Freedom Mortgage turned to Bigeye: “Data observability, and, more importantly, Bigeye, was the solution to that problem,” Eric noted.

By providing transparency across their data environment, Bigeye enabled Freedom Mortgage to not only monitor its critical data assets, but also gain visibility into the larger data landscape.

“Bigeye brings all of that data into a centralized pane of glass, so to speak,” said Eric. “It puts it all in a place where it's very easy to understand, it's very easy to monitor, and it's very easy to track.”

This centralized approach allowed Freedom Mortgage to scale its governance efforts without adding more resources or manual processes.

When it came to choosing a data observability solution, knowing what to look for was key. Bigeye’s Complete Guide to Data Observability in 2024 outlines the essential factors for selecting the right vendor, trends to watch, and practical recommendations for your organization.

The Vendor Selection Process: Why Bigeye?

Selecting the right partner for this data transformation was crucial. Eric and his team considered a wide array of data observability vendors, but Bigeye stood out for three key reasons:

  1. The ability to monitor data at a high level of scale
  2. The ability to apply granular data quality rules at the bottom of the funnel
  3. The ability to trace data lineage from its origin to its final destination

“There were about a dozen vendors in the data observability space whom we spoke with,” Eric explained. “Out of that list, there were two that checked all our boxes. What made Bigeye stand out was that they were eager to partner with us.”

Bigeye’s willingness to collaborate closely with Freedom Mortgage, rather than just provide a product, made them the clear choice.

The Impact: Efficiency and Transparency

Since implementing Bigeye, Freedom Mortgage has seen significant improvements: “The biggest impact is that it’s providing that transparency,” said Eric. “The question has always been: What does the top of the funnel look like? We couldn’t answer that before. Bigeye has provided us with that transparency and insight into all the data that’s fed into Freedom Mortgage.”

With a clearer view of their data, Freedom Mortgage can ensure data quality and consistency, across its operations: “Bigeye is helping us to be much more efficient and effective, because we’re able to monitor the quality of the data, so it’s accurate the first time—every time,” Eric added.

This not only improves internal processes, but also enhances the experience for customers by making the entire mortgage process more efficient.

The Future of the Partnership

Looking ahead, Freedom Mortgage plans to expand its use of Bigeye across even more areas of the organization: “We’ll continue to utilize Bigeye and roll it out to Freedom Mortgage’s extended data audience,” Eric shared.

With Bigeye’s support, Freedom Mortgage can continue scaling its data governance strategy without adding more manual effort or headcount.

The Big Picture

By partnering with Bigeye, Freedom Mortgage has been able to overcome the limitations of traditional data management methods and gain full transparency into its data landscape.

“The value that we’re looking for Bigeye to bring to Freedom Mortgage is the ability to govern at scale,” said Eric.

With Bigeye’s continued partnership, Freedom Mortgage is well-equipped to meet the data challenges of both today and tomorrow.

Discover how Bigeye can help you achieve the same transparency and efficiency in your data operations. Explore our case studies to see how we’ve helped other companies, or get a personalized demo and learn how we can support your data management needs. 

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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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