BDBurleigh Data Co

Selected work

Challenges met.
Problems solved.

A selection of real-world implementation patterns across custom applications, integrations, ontology design, and operational workflows.

These examples are intentionally generalized. Organization names, industries, internal systems, identifying metrics, and proprietary business details have been omitted to protect confidentiality.

01
React · OSDK · Ontology

The full portfolio in one operational view

A custom React application that gave each user a previously unavailable view across everything they managed, with related context and actions in one place.

The problem

Account managers had no single view of the full scope of their portfolios. Related records and signals existed across different systems, but the overall picture was unavailable to the people responsible for the work.

The approach

Designed a custom React application on the Ontology SDK, using the ontology to connect the relevant records and relationships. Built the interface around a complete portfolio view, with operational context and next-step workflows close at hand.

The outcome

For the first time, each user could see their entire portfolio and how its parts related, with the context and actions needed to work across it in one application.

  • Custom React frontend
  • Ontology SDK
  • Relationship-aware interfaces
  • Operational workflow design
02
APIs · PySpark · Incremental ingestion

Replacing a heavy integration with a focused data pipeline

A custom API-based ingestion pattern that retrieves only necessary data, handles historical backfills, and keeps later updates lightweight.

The problem

A ready-made integration brought in substantially more data than downstream users needed. Broad extraction made processing harder to manage and created unnecessary complexity for everyday refreshes.

The approach

Built a targeted API integration with a deliberate historical backfill strategy, incremental updates, bounded pagination, deduplication, and careful handling of source-specific time semantics.

The outcome

A cleaner, more maintainable ingestion pattern that separates one-time historical loading from routine updates while giving downstream pipelines a narrower and more useful source dataset.

  • Custom API integration
  • Partitioned historical loading
  • Incremental synchronization
  • Idempotent processing
03
Ontology · Evidence modeling · Governance

Connecting fragmented signals into an investigation workflow

A governed workflow that combines related signals from multiple systems into a clearer, reviewable operational picture.

The problem

Potentially related events were appearing in different systems, each with its own structure, timing, and level of reliability. Reviewing them independently made it difficult to understand the complete situation.

The approach

Created a common model for related evidence, linked source records through the ontology, and designed an investigation-oriented workflow with appropriate access controls and human review points.

The outcome

A more consistent foundation for connecting signals, reviewing supporting context, and managing follow-up without treating every individual system event as a final conclusion.

  • Cross-system data modeling
  • Ontology relationships
  • Investigation workflows
  • Sensitive-data governance
04
Automations · Actions · Operational design

Turning important events into actionable workflows

An end-to-end alerting pattern that translates qualifying events into governed, role-appropriate actions for the people responsible for follow-up.

The problem

Important operational changes could be detected in source data, but the relevant teams did not have a dependable way to identify what needed attention or understand what to do next.

The approach

Built a workflow spanning transformation logic, durable event identity, ontology-backed records, governed actions, and scheduled automation. Designed the process to support staged rollout and operational readiness.

The outcome

A repeatable pattern for delivering relevant events to the appropriate users with clearer ownership, more useful context, and a practical path from detection to follow-up.

  • Event-driven data pipelines
  • Foundry Automate
  • Ontology actions
  • Controlled production rollout

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Available for focused projects, implementation support, and hands-on consulting engagements.

nick@burleighdata.com