Anna Kónyi

• • Designed and developed Power BI dashboards and reports to deliver data insights to various departments, enabling beter business decisions, and KPI monitoring.

• • Built tabular data models (star schema) and DAX measures to enhance analytical capabilities and reporting flexibility.

• • Connected Power BI to a variety of sources; performed data extraction, transformation, and dimensional modeling for business-intelligence reporting.

• • Performed data analysis using Python, including data cleaning, transformation, and visualization to uncover business trends.

• • Collaborated with stakeholders to translate business requirements into dashboards and data solutions within Agile project environments.

• • Worked with relational databases and data lakes to access and manage large datasets efficiently.

• • Leveraged AI assistants (Claude, ChatGPT, GitHub Copilot) for SQL and Python development, automated data cleaning script generation, and Power BI documentation - accelerating routine analyst tasks by ~30%.

• • Wrote SQL queries for data retrieval, aggregation, and performance optimization.

• • Created detailed Excel reports with dynamic charts, pivot tables, and data models to support operational and strategic needs. Achievements:

◦ • Designed and shipped a Power BI report on Veeva CRM data serving 420 active users; engineered the tabular model and DAX measures to deliver sub-second filtering across multi-million-row tables.

◦ • Built a dashboard consolidating 8 separate Excel sources into a unified plant-efficiency report covering production volumes, machine operating/downtime, workforce levels, and defined KPIs.

◦ • Re-architected the product portfolio analysis pipeline (SQL + Power Query + Power BI), cuting end-to-end refresh time by 20% and eliminating manual Excel steps.

• • Extracted data from medical databases to generate reports and support health research.

• • Data extraction from medical histories, which supported the processing of unstructured medical texts in the field of lung and prostate cancer

• • A/B Testing

• • Analyzed real-world data (RWD), particularly in processing health-related text, using advanced text analysis techniques such as regular expressions.

◦ • Reduced anamnesis processing time by 30% through NLP and regex-based automation.

public transport data

• • Analyzed Hungary's long-distance bus network to identify timetable inefficiencies and route overlaps.

• • Modeled passenger flow and stop-level data with SQL.