Beyond Flat Lists: The Graph Model
Traditional CRM and spreadsheet tools organize data in rows and columns: a list of contacts, a list of companies, a list of deals. This flat model works for simple sales pipelines but completely fails when you need to understand connections. A person is a director of three companies, one of which owns a subsidiary that holds a real estate asset managed by another person who also sits on the board of a foundation — and you need to see all of this at once. This is what relationship mapping software is built for.
How the Graph Database Works
Under the hood, relationship mapping software uses a graph data model rather than a purely relational one. Every person, company, asset, and document is a node. Every connection — "is director of," "owns," "is subsidiary of," "is managed by," "signed document X" — is an edge between nodes. This graph structure allows the software to answer questions that are expensive or impossible in flat SQL:
- "Show me every entity within three degrees of connection to this person."
- "Which assets are ultimately controlled by this family trust, through however many intermediate holding companies?"
- "Are there any shared directors between these two apparently unrelated companies?"
- "Who would be affected if this key individual were to step down from their roles?"
Visual Exploration vs Static Reports
The interactive graph view is the primary differentiator. Instead of running a report and reading a table, you navigate the relationship network visually:
- Start from a person or entity you know.
- Expand connected nodes to reveal direct relationships.
- Click any node to make it the new center and expand further.
- Apply filters to show only certain relationship types or entity categories.
- Zoom out to see the macro structure or zoom in to examine a specific connection chain.
This exploratory approach often surfaces connections that you would never think to query for explicitly — the "unknown unknowns" that matter most in due diligence and intelligence work.
Practical Use Cases
M&A Due Diligence: Map the target company's full ownership structure, identify all subsidiaries and their directors, cross-reference against your existing knowledge base to flag conflicts or risks.
Family Office Wealth Tracking: Build the complete picture of a family's holdings — operating companies, holding structures, trusts, real estate, investment portfolios — and see how assets relate to family members across generations.
Corporate Intelligence: Track competitors, suppliers, and partners. Map their organizational structures, key personnel movements, and business relationships to inform strategic decisions.
Investigation and Research: Connect people to entities to addresses to documents. As new information arrives, add it to the graph and immediately see how it changes the relationship picture.
Running Relationship Mapping Locally
ONS Data Terminal includes an interactive relationship graph as a core feature, running entirely on your local machine. The graph data is stored in your local PostgreSQL database — no graph data is sent to any external service for processing or rendering. This matters because the relationship map itself is often the single most sensitive artifact in an investigation or deal process.