Pie Insurance

Data as the Core of Insurance

At Pie Insurance, growth isn’t just about policies – it’s about data. In the world of insurtech, data is the product. Every decision, from underwriting to claims management to new business expansion, depends on accurate, trusted, and accessible data.

But a few years ago, Pie faced a common challenge: trust in the data warehouse was low, silos slowed progress, and scaling new lines of business threatened to create bottlenecks. The company needed a foundation that would allow them to move fast without sacrificing governance.

That’s where two leaders stepped in: Ed Presz, Director of Data Engineering, and Kenneth Wood, Staff Data Engineer and the main Architect. Their vision for a data-first culture transformed how Pie approaches data modeling and architecture, laying the groundwork for future growth.

The Visionaries Behind the Transformation

Ed Presz: Building a Center of Excellence

Ed oversees Pie’s 15-person data engineering organization, spanning architecture, analytics, platform, and machine learning engineering. But his role is bigger than just managing teams. Ed says his leadership philosophy is rooted in a simple truth: “Our data is the product.”

Recognizing that trust in the warehouse was non-negotiable, Ed established what he calls a “center of excellence.” His goal wasn’t to centralize control but to empower his teams. By creating standards, repeatable patterns, and a culture of “teaching to fish,” Ed ensured that everyone at Pie – not just a few architects – could confidently build and extend the data platform.

Ken Wood: Architecting the Future

If Ed provided the vision, Ken built the blueprint. As one of Pie’s key architects, Ken led the shift from Enterprise Data Warehouse 1.0 (EDW1) to its improved version (EDW2), introducing a core industry-standard model that serves as the foundation for Pie’s data strategy. His fingerprints are on every part of the system, from table design to pipeline architecture.

Ken’s mantra, “It’s always about the data”, shaped Pie’s approach to data modeling and design. Instead of patchwork solutions or one-off fixes, Ken focused on designing a model that could grow with the business. When Pie added a new line of business, Commercial Auto Insurance, the team didn’t have to start from scratch. Thanks to Ken’s forward-thinking design, they simply extended the core model, which allowed them to save time, reduce friction, and accelerate time-to-market for the reporting foundation of this new business line.

The Challenge and SqlDBM’s Role as the Ally

Before the rebuild, Pie Insurance’s enterprise data warehouse (EDW1) struggled with two critical issues: low trust and slow delivery. Business users doubted the accuracy of reports, making it hard to rely on data for strategic decisions. At the same time, every new table or change had to go through a small group of architects, creating bottlenecks and slowing time-to-market.

This is where Ed’s leadership and Ken’s architecture came into play. They envisioned a culture where the architecture team acted as a center of excellence, setting standards and patterns, but empowering engineers across the organization to build confidently without hand-holding. As Ken put it: “We don’t want to be a bottleneck. It’s about teaching people to fish.”

To bring this vision to life, they leaned on SqlDBM. The platform didn’t just solve the problem for them, it enabled them to execute their strategy:

Collaboration at Scale: SqlDBM gave every team member visibility into the models, creating a shared language between architects, engineers, and business stakeholders.
Industry-Standard Design: With SqlDBM, Ken could document and extend the core insurance model, ensuring every new line of business fit into the bigger picture.
Agility with Governance: Ed’s goal of balancing speed and trust was supported by SqlDBM’s versioning and visualization, allowing engineers to move quickly without losing oversight.

Together, their leadership and SqlDBM’s capabilities transformed Pie’s data warehouse from a source of doubt into a trusted foundation for business growth.

Impact and Results

The results of Pie Insurance’s data warehouse transformation were clear, and they all point back to Ed’s leadership and Ken’s architectural foresight.

Faster Expansion into New Lines of Business

When Pie launched Commercial Auto alongside its core Workers’ Compensation offering, the data team didn’t have to start from scratch. Thanks to Ken’s core industry-standard model, they simply extended the framework, enabling faster reporting and analytics across multiple business lines. What could have taken months was reduced to weeks.

Seamless Integration of Third-Party Systems

In the insurance space, many core functions like claims are handled through specialized vendors. Pie initially worked with Corvell, then transitioned to Origami. With a robust data model in place, the switch was virtually plug-and-play. This strategy of building standards meant the data model “didn’t miss a beat”, according to Ed.

Restored Trust in Data

Perhaps the most critical outcome: executives and business stakeholders now trust the numbers they see. As Ed explained, before the transformation, reports weren’t widely believed. Now, decisions about loss ratios, growth trends, and even IPO-readiness rest on a foundation of accurate, consistent data.

Agility Without Bottlenecks

By empowering engineers across the org with patterns and guidance, Ed and Ken avoided the trap of becoming bottlenecks. SqlDBM’s collaborative modeling environment supported this vision, giving visibility and clarity while maintaining governance. Engineers could build with confidence, and leadership could trust the outcomes.

The transformation wasn’t just technical. It was cultural. Pie Insurance shifted from “data as a burden” to “data as the product”, a mindset led by Ed and Ken, powered by SqlDBM.

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Pie Insurance

Data as the Core of Insurance

The Visionaries Behind the Transformation

Ed Presz: Building a Center of Excellence

Ken Wood: Architecting the Future

The Challenge and SqlDBM’s Role as the Ally

Impact and Results

Faster Expansion into New Lines of Business

Seamless Integration of Third-Party Systems

Restored Trust in Data

Agility Without Bottlenecks

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Resources

Strategic advisors

Kent Graziano

Gordon Wong

For cloud data platforms

Try modeling now

Platform

Data Modeling

Model Governance

Snowflake Schema Monitoring

Integration

See all

Why SqlDBM?

Have questions?