Welcome to the repository powering data_frank, the professional portfolio of Frank Ellingsen.
With a background in Finance & Business Administration, I specialize in the intersection of financial governance, engineering project controlling, and modern business intelligence. My focus is delivering high data-ink reporting—eliminating visual clutter to surface critical cost and schedule variances before they impact the bottom line.
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📐 Project Controlling & Earned Value Management (EVM)
Performance indices (CPI, SPI), Estimate at Completion (EAC) & Estimate to Complete (ETC) forecasting, cost/schedule variance tracking, and Gantt milestone management. -
📊 Business Intelligence & Data Modeling
Enterprise data modeling, DAX measure engineering, Power BI interactive reporting, Microsoft Fabric lakehouse architecture, and Power Query ETL. -
🧱 Data Engineering & Analytical SQL
Lightweight analytical architectures using DuckDB for analytical workloads, SQLite for transactional tables, and automated Python pipelines. -
🤖 Applied AI & Agentic Orchestration
Autonomous multi-agent research systems (Planner → Researcher → Synthesizer), report synthesis, and local-first LLM workflows (Ollama, LangChain). -
🖋️ Data Visualization Standards (Edward Tufte)
High Data-Ink Ratio: direct S-curve labeling, removal of decorative chart junk, and clear, right-aligned tabular metrics for executive decision clarity.
| Domain | Primary Tools & Technologies |
|---|---|
| Project Controlling & BI | Microsoft Power BI, DAX, MS Fabric, Microsoft Excel (Power Query, Advanced Modeling), Tableau |
| Data & Databases | DuckDB, SQLite, SQL Server, PostgreSQL |
| Programming & Scripting | Python (Pandas, NumPy, scikit-learn), JavaScript (Vanilla, React) |
| AI & Automation | Agentic AI Multi-Agent Workflows, REST APIs, Local LLM Inference (Ollama) |
- Focus: Energy Market Back Office, Project Controlling, EVM Simulation, 52 Hydropower Plants, Isolation Forest ML, DuckDB/SQLite OLAP/OLTP Engine
- Description: Full-scale Power Market Back Office and Project Controller platform engineered for portfolio anomaly detection, hydropower generation monitoring (52 plants across NO1, NO2, and NO5 price zones), and physical power imbalance settlement. Features dynamic EVM-style imbalance risk simulation (BAC/AC/ETC/EAC), interactive S-Curves with direct labeling, an Isolation Forest machine learning anomaly detection engine for SCADA telemetry faults, and an in-browser DuckDB/SQLite analytical SQL studio.
- Repository: Power-Market-Back-Office
- Focus: Python, Pandas, Power BI, Time Series Econometrics, NO1–NO5 Bidding Zones
- Description: Longitudinal econometric analysis of spot electricity prices across Norway's five bidding zones (NO1–NO5). Investigates seasonal fluctuations, grid transmission constraints, and structural price disparities between southern and northern regions.
- Repository: norwegian-electricity-analysis
- Focus: Autonomous Project Controlling, Defense & Maritime, EVM S-Curves, IFRS 15 / IAS 37 Compliance, 19 WP Gantt, 5x5 Risk & VOR Governance
- Description: Autonomous PMO and Project Controlling platform engineered for naval defense lifetime extension programs (Skjold-Class Stealth Fast Patrol Boats at Umoe Mandal). Integrates full-lifecycle executive governance, interactive triple S-Curve EVM forecasting (BAC 766M NOK, CPI/SPI indices), 19 Work Package milestone Gantt scheduling, drydock execution tracking, IFRS 15 / IAS 37 accounting compliance, and Variation Order Request (VOR) governance.
- Repository: AI-AGENTIC-PMO
- Focus: Microsoft Fabric (Direct Lake), Project Controlling, EVM, S-Curves, Risk & VOR Governance
- Description: Enterprise PMO and Earned Value Management platform built on Microsoft Fabric Lakehouse for naval defense construction (Skjold-Class Stealth Patrol Boats). Features triple S-Curves, CPI/SPI indices, WBS Gantt scheduling, EMV risk matrix, and VOR governance adhering to Edward Tufte Data-Ink principles.
- Repository: PMO-EVM-Analytics-in-Microsoft-Fabric
- Focus: Project Controlling, Earned Value Management (EVM), S-Curves, Schedule Variance
- Description: Interactive EVM and Gantt control system for industrial offshore construction. Analyzes cost variance (CV), schedule variance (SV), and earned schedule (ES) with high data-ink efficiency.
- Repository: North-Sea-Oil-Platform-Drill-Tower-Construction
- Focus: Multi-Agent Systems, Autonomous Research, Decision Intelligence
- Description: Autonomous 3-tier AI research architecture (Planner → Researcher → Synthesizer) aggregating multi-source evidence and generating structured executive intelligence dossiers.
- Repository: 3-Layer-Agentic-AI-Topic-Researcher
- Focus: Financial Control, CPI/SPI Tracking, EAC/ETC Forecasting
- Description: Interactive financial management interface tracking budget burn rates, cost indices (CPI/SPI), and projecting estimate at completion (EAC).
- Repository: Project-Mangagement
- Focus: Microsoft Stack, Power BI, Predictive Demand Modeling
- Description: Full-stack BI solution transforming car rental fleet operations through utilization tracking, pricing strategy evaluation, and predictive modeling.
- Focus: Python, scikit-learn, Regression Modeling
- Description: Supervised regression pipeline modeling residential property valuations based on square footage, location indicators, and property attributes.
- Email: frankellingsen@hotmail.com
- LinkedIn: linkedin.com/in/frankellingsen9117
- GitHub: github.com/Frank-Ellingsen
- Maven Analytics: mavenshowcase.com/profile/983173e0-a031-703c-17f4-1735934f6826
Portfolio codebase maintained with high data-ink design standards.