Behnam Ebrahimi, Senior BI Analyst
Analytics that supports real decisions
I'm Behnam Ebrahimi, Senior BI Analyst focused on healthcare analytics, Power BI & Microsoft Fabric, forecasting, SQL, and practical applied AI.
Building trustworthy numbers, clear visuals, and automation that holds up under scrutiny.
11 projects, 40 articles, and an AI playbook. Start with the work or the writing.
Healthcare BI
Operational and clinical reporting, forecasting, and decision support with governance in mind.
Analytics engineering
SQL models, metric definitions, and pipelines that make dashboards reliable instead of fragile.
Power BI & Fabric
Semantic models, DAX, performance, and reporting design for people who need to act.
Applied AI
Workflows and tools that use AI where it helps, with clear limits, auditability, and human review.
Selected work and writing
Projects
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Emergency department demand forecasting
Daily attendance forecasts 28 days ahead from three models and an average, scored with a rolling-origin backtest across 2025 and given 80% intervals built from past errors.
Healthcare BI -
30-day readmission risk model
A readmission risk score for a discharge team that can only call so many patients, tested on a time split for calibration, subgroup performance and a planted data leak.
Applied AI -
Referral-to-treatment waiting list semantic model
A Power BI semantic model written in TMDL for RTT waiting list reporting, with a weekly snapshot fact, a pathway fact, 18 DAX measures and the same KPIs reproduced in pandas on synthetic data.
Power BI & Fabric -
Outpatient analytics pipeline
A dbt-style SQL pipeline on SQLite that turns a messy outpatient extract into tested marts, with data tests that catch the planted problems and every rate defined once in YAML.
Analytics engineering -
Bed occupancy simulation
A discrete-event simulation of 120 acute medical beds on synthetic data, run for 200 simulated years per scenario to test earlier discharges, weekend discharging and 5% more demand.
Healthcare BI
Latest writing
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MCP servers for data work
What the Model Context Protocol is, how Claude Code connects to MCP servers, three patterns for analytics teams (read-only database access, documentation lookup and ticketing), and the governance that has to come first.
AI workflows & prompting -
Choosing a Claude model and effort level for analytics work
How to pick between Fable, Opus, Sonnet and Haiku and between effort levels for lookups, routine SQL, hard debugging and long builds, and how to make the choice a habit.
AI workflows & prompting -
Reviewing AI-written DAX and SQL
A review checklist for AI-generated SQL and DAX, with wrong and right pairs for each trap and a small fixture that catches the mistakes before a stakeholder does.
AI workflows & prompting -
Subagents and parallel work in Claude Code
When to split work across Claude Code subagents, how to brief them, how to stop them racing each other, and how to check the result before anything ships.
AI workflows & prompting
Contact
[email protected]Email for work enquiries and questions about anything on this site. LinkedIn for professional introductions.