Platform
Case Studies
A Midsized Financial Tech Company
Breaking the Clone-and-Scrub Cycle
How a fast-growing fintech eliminated data duplication and enabled safe internal data sharing—with visibility into who's using what.
The Company
A midsized financial technology company that grew quickly over recent years. With rapid growth came "big company" growing pains—particularly around how internal teams discovered, accessed, and reused data across the organization.
Engineering teams had built powerful data systems, but the organization lacked a unified way to share that data internally. Teams often didn't know what data was available, or couldn't access it safely due to PII concerns.
Rapid Growth
Multiple teams building independently, creating data silos
Rich Data Assets
Valuable datasets scattered across teams and systems
The Challenge
Discovery Problem
Teams didn't know what data was available across the organization. Without a central catalog, engineers often built from scratch rather than reusing existing data sources.
Duplication Spiral
When teams did find relevant data, it often contained PII they couldn't access. The solution? Clone the dataset and manually scrub it—creating drift, inconsistency, and compliance risk.
The Hidden Risk
Data duplication exposed the company to problems down the road. If manually scrubbed data wasn't properly cleaned, PII could leak. And the owning team lost visibility into who was using their data and how.
The DataHarbor Approach
Instead of building a custom data catalog or forcing teams through manual approval processes, the company enrolled with DataHarbor to create a governed internal data marketplace.
Teams Published Their APIs
Data-owning teams enrolled their APIs and datasets with DataHarbor. Each team could then release their data onto a private company marketplace—with governance controls they defined.
Multiple Virtual APIs Per Dataset
Tiered Access Levels
- Full PII View: For teams with legitimate need and approval
- Anonymized View: Safe for broad internal consumption
- AI-Ready View: Tokenized for internal LLM use cases
Owning teams released several Virtual APIs for each dataset—some with full PII for approved use cases, others with varying levels of protection for safer consumption.
Governed Discovery and Consumption
Private Marketplace
- Searchable: Teams can discover available data internally
- Pre-governed: Data is already OK for consumption at each tier
- Approved: Owning teams can monitor and approve use cases
Now teams could search and discover data across the organization. They could safely use it knowing the governance was already applied—and owning teams maintained visibility into who was accessing their data.
Continuous Schema Protection
Fathom Schema Monitoring
- Protected views: Lighter monitoring for known PII use cases
- Safer views: Strict monitoring with auto-remediation or cutoff
- Alerts: Flag new fields that could contain PII
DataHarbor's schema monitoring protected against accidental PII leaks. Views intended for broad consumption could be configured for automatic remediation or cutoff if protected data appeared unexpectedly.
The Outcome
Duplication Eliminated
True data duplication became rare. Teams reused governed data instead of cloning.
PII Protected
Another layer of defense against internal PII leaks with schema monitoring.
Teams Accelerated
Internal visibility helped teams find and use existing data faster.
AI-Ready Data
Greenfield projects quickly found safe data via MCP for AI use cases.
DataHarbor Capabilities Used
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