The workflow before
FJ Capital Management manages more than $1B, with trade and position data spread across its AlphaDesk order management system, fund administrator files and Excel sheets. One employee ran SQL queries by hand each day and refreshed Power BI, so reporting stopped when that person was out. The dashboards had also hit the Power BI Pro ceiling of about 350K rows, which meant the team could only see part of its own history.
What we built
We built a Microsoft Fabric lakehouse that pulls trade and position data from the AlphaDesk API automatically and moves it through bronze, silver and gold layers. The logic that used to live in one person's head is now written down as infrastructure as code.
We rebuilt the Power BI dashboards to run on the full 8-year history, more than 1.5M rows, without lag. Daily P&L attribution by portfolio manager and by sector now produces itself each morning instead of waiting on a manual run.
Before and after
| Measure | Before | After |
|---|---|---|
| History in dashboards | About 350K rows (Power BI Pro limit) | 1.5M+ rows, full 8 years |
| Daily P&L attribution | Manual SQL and refresh by one employee | Automated every day, by PM and sector |
| Key person dependency | One person held the reporting logic | Logic in code, runs without them |
What's next
Trade, position and P&L data now sit in one governed lakehouse. That is the foundation for L2 work: an analytics assistant that lets portfolio managers ask about attribution and exposure directly instead of waiting for a report.
