M.Sc. Web & Data Science · University of Koblenz
Data Analytics · SQL · Power BI · Business Intelligence
M.Sc. Web & Data Science student at the University of Koblenz with professional and academic experience in data analytics, SQL reporting, business intelligence, structured data processing, data transformation, and data-quality workflows.
My current focus is on Data Analytics and Business Intelligence, using SQL, Power BI, Power Query, DAX, Excel, and relational data to transform raw information into structured analysis, KPIs, reports, and decision-support insights.
Python and machine learning remain supporting technical skills developed through academic, research, and analytical projects.
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University of Koblenz · Germany Graduate studies covering data science, analytics, machine learning, databases, web technologies, and applied research. |
Kumaraguru College of Technology · India Undergraduate foundation in computer science, databases, programming, software systems, and applied computing. |
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Karlsruhe Institute of Technology (KIT) Worked with structured research datasets, supporting data collection, transformation, validation, documentation, and data-quality workflows. Focus Data Processing · Data Transformation · Data Validation · ETL Workflows · Data Quality · FAIR Data Principles |
Tata Consultancy Services (TCS) Worked with operational datasets, SQL-based analysis, Power BI reporting, and data-migration activities in enterprise environments. Focus SQL · Power BI · Data Analysis · Reporting · Data Migration |
| Analytics & BI | Data & Quality | Supporting Technical Skills | Research & ML Exposure |
|---|---|---|---|
| SQL | Data Cleaning | Python | Model Evaluation |
| Power BI | Data Transformation | Pandas | PyTorch |
| Power Query | SQLite | NumPy | OpenCV |
| DAX | ETL Concepts | Git / GitHub | YOLO |
| Excel | Data Validation | Linux | Transformers |
| KPI Analysis | Data Quality | Jupyter | Computer Vision |
| Reporting | Structured Data | VS Code | NLP Research |
| Data Visualization | Relational Data | Matplotlib | Document AI |
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Business-oriented analysis of German manufacturing performance using official Destatis GENESIS-Online data covering all 16 German federal states from 2019 to 2025. Focus
Stack SQL · SQLite · Power BI · Power Query · DAX · Excel |
End-to-end football analytics project covering match, team, and player analysis for the 2025/26 UEFA Champions League. Focus
Stack SQL · SQLite · Python · Pandas · Matplotlib |
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Data-processing and quality-analysis pipeline for regulatory PDF documents. The project reconstructs and extends work from a Master's Research Lab project while keeping the portfolio implementation reproducible and lightweight. Focus
Stack SQL · SQLite · Python · Pandas · PyMuPDF · Matplotlib |
Research project evaluating table-detection and table-structure-recognition approaches for historical regulatory document images. Focus
Models YOLOv8 · YOLOv10 · YOLOX/Nemotron · Table Transformer Stack Python · PyTorch · OpenCV · Hugging Face Transformers Repository currently private during thesis submission. |
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Research seminar examining automated ICD coding from clinical text using transformer-based NLP approaches. The project focuses on analysing published methods and reported experimental evidence rather than presenting a personal model implementation. Focus
Topics BioBERT · ClinicalBERT · BERT-based ICD Coding · Transformers · ICD Classification |
Bachelor final-year group project implementing a smart-parking prototype based on automatic vehicle number-plate recognition. Focus
Stack Python · OpenCV · Pytesseract · Raspberry Pi |
SQL · Power BI · Power Query · DAX · Excel · KPI Analysis · Reporting · Data Visualization
Data Cleaning · Data Transformation · SQLite · Structured Data · ETL Concepts · Data Validation · Data Quality
Python · Pandas · Git · Machine Learning Evaluation · Computer Vision · Document Analysis · NLP Research
My portfolio is currently focused on practical data-analysis workflows that demonstrate:
- working with real-world and official datasets;
- cleaning and transforming raw data;
- querying structured data with SQL;
- developing KPIs and analytical metrics;
- building Power BI dashboards and reports;
- validating data quality and analytical outputs;
- communicating findings through clear visualizations and documentation.