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Investment Firm Database Work
Database work for an investment firm that needs one trustworthy set of records for its assets, deals and partners.
Business goals
The client is a private investment firm with interests in real estate and related assets. Firms like this make long-term decisions from property records, underwriting figures, financing terms and partner information. When that data is scattered across spreadsheets and aging files, two people can report two different numbers for the same asset. The client needed database work that gave its information a sound structure, and that made it easier to find and trust when decisions were being made.
Project overview
Hexagon carried out database work for the client, focused on structure, data quality and access. We organized information around the things an investment team tracks: assets, deals, financing and partners. Duplicate and inconsistent entries were identified for cleanup, and existing data was brought across into the new structure. Queries and reports then gave staff repeatable answers. Access rules kept sensitive financial and investor details limited to the right people.
Challenges faced and solved
Investment decisions deserve data that everyone in the room agrees on.
Different numbers for the same asset
When several analysts keep their own spreadsheets, an asset's value or occupancy can differ from file to file. Meetings then get spent settling which number is right, not what it means.
We defined one structure for core asset and deal records, so each figure has a single home that every report can draw from.
Data quality built up over years
Deals done long ago were recorded in whatever way suited that moment. Names vary, fields are blank and duplicates accumulate, and each of these makes any report across the portfolio unreliable.
We reviewed existing records for duplicates and inconsistent values, then standardized them as part of moving the data into the new structure.
Slow answers to simple questions
A partner asks about exposure across a group of holdings, and someone spends a day assembling it by hand. Questions that recur should not need fresh manual work every time.
We wrote repeatable queries and reports for common questions, so staff can get an answer from the database without rebuilding a spreadsheet.
Sensitive information in too many places
Investor details and financing terms need careful handling. Copies emailed around or saved on individual machines are hard to control, and nobody can say with confidence who has seen what.
We set role-based access on the database, so sensitive records stay in one controlled location and each person sees what their role requires.
Features
| Feature | Description |
|---|---|
| Investment and asset teams | |
| 1. Asset Records | Each holding has a consistent record of property details, status and key dates. |
| 2. Deal Records | Acquisitions and financings are stored with their terms and references to related documents, so past decisions can be reviewed. |
| 3. Financing Details | Lender, term and maturity information is held in a structured way, so upcoming dates can be listed instead of hunted down. |
| 4. Repeatable Reports | Standard portfolio queries return the same logic each time, which removes arguments over method. |
| Investor relations staff | |
| 5. Partner and Investor Records | Contact and commitment data sit in one place, linked to the deals they relate to. |
| 6. Controlled Access | Sensitive partner information is limited by role. |
| Technical and operations staff | |
| 7. Database Schema Design | Tables and relationships are designed around how the firm actually thinks about assets and deals. |
| 8. Data Cleanup | Duplicates and inconsistent names are identified and standardized, so reports can be trusted. |
| 9. Data Migration | Existing information is moved from older files into the new structure, with checks to compare before and after. |
| 10. Backup and Recovery | Backups and a tested restore routine protect records the firm can't afford to lose. |
| 11. Query Tuning | Slow queries and missing indexes are addressed, so reports respond promptly as the data grows. |
How the platform is put together
Each layer has one job.
The result
The client's core records now sit in a cleaner, better-organized database. Staff have a clearer path to answers they can repeat and defend.
| Area | Before | After |
|---|---|---|
| Core figures | Copies held in separate files | One structured home for each record |
| Data quality | Duplicates and inconsistent names | Standardized records after review |
| Common questions | Assembled by hand | Repeatable queries and reports |
| Sensitive data | Copies harder to control | Role-based access in one place |
How we took it from idea to launch
Good software follows a process. Here are the six stages, and what happens in each one.
Discovery & Requirements
Goal: Define the product vision, target audience and core business requirements.
Key activities- Stakeholder interviews
- Market and competitor research
- Defining user personas
- Drafting technical specifications or a Product Requirements Document (PRD)
Design (UX / UI)
Goal: Create an intuitive user experience and visual interface.
Key activities- UX design: information architecture, user flows and wireframes
- UI design: high-fidelity mockups and interactive prototypes in Figma or similar tools
- Design system: colors, typography and component libraries
Development: Frontend & Backend
Goal: Build the functional application using agile sprints.
Key activities- Backend: set up databases, design APIs (REST, GraphQL), implement server logic, and configure authentication and authorization (OAuth, RBAC)
- Frontend: build responsive interfaces and connect components to backend APIs
- Version control: manage code through Git and GitHub
Security & Optimization
Goal: Harden the application against vulnerabilities and boost performance.
Key activities- Security: address the OWASP Top 10, including injection, XSS and CSRF, enforce encryption in transit and at rest, and implement rate limiting
- Optimization: code splitting and lazy loading, database indexing, API caching and load testing
- QA and testing: unit, integration and end-to-end tests
Beta Release
Goal: Deploy to a controlled group of real users to catch edge-case bugs and gather feedback.
Key activities- Set up staging and production CI/CD pipelines
- Launch a closed or open beta with real users
- Monitor errors through observability tools
Public Release (Launch)
Goal: Roll the software out to the general public.
Key activities- Final production deployment
- DNS configuration
- Marketing and onboarding rollout
- Post-launch performance and security monitoring
Business benefits
Discussion can focus on the decision, not on whose spreadsheet is right.
Recurring questions no longer begin with a blank spreadsheet.
Sensitive records stay in one governed place.
Future dashboards and applications have clean data to draw from.
Conclusion
Good investment judgment needs dependable information behind it. Hexagon's database work gave the client a sounder structure for its records, cleaner data and repeatable ways to get answers. None of this is glamorous, but it sits underneath every report and meeting that follows. If your firm's numbers live in too many files, or a simple portfolio question still takes a day to answer, tell us about it. We're happy to take a look at your data and talk through what could help.
Talk to us about your projectRelated services: database services · custom software development
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