Dmitry Kuvyrdin

Data & Business Analyst

Your Data Expert

Business-focused Data Analyst with expertise in SQL, Tableau, Python, and Excel, experienced in analyzing revenue, customer behavior, and operational performance. I design SQL-based workflows and interactive dashboards that turn complex relational datasets into actionable business insights. Skilled in KPI development, trend analysis, and business intelligence reporting, I help organizations make smarter, data-driven decisions that drive measurable impact.

CERTIFICATIONS

  • Google Data Analytics

  • Google Digital Marketing & E-Commerce

  • Marketing Analytics with University of Virginia

  • Data Vizualization with Tableau

Analytics Projects

Here are my data analytics projects, showcasing hands-on work across business and e-commerce use cases. Each project demonstrates my ability to clean and model data, analyze trends, and translate insights into clear, stakeholder-ready visualizations and recommendations.Please explore my data projects below.

This project analyzes logistics network performance, profitability, and operational efficiency for a simulated Class 8 trucking company.Using SQL and Tableau, I examined route profitability, fleet utilization, revenue trends, and cost efficiency to identify the key drivers of logistics performance and opportunities for operational optimization.Below are the key insights from the analysis.

  • Strong margins: Profit margins average 82–86% across routes, with top-performing lanes reaching 93%.

  • Cost efficiency: Only 14–18% of revenue goes to variable costs (fuel and maintenance).

  • Optimization opportunities: A small number of routes are loss-making, indicating potential for rerouting or repricing.

  • Improving efficiency: Cost per mile is decreasing while profit per mile continues to rise.

This project analyzes pharmacy sales performance, profitability, and promotional effectiveness across products, pharmacies, regions, and time.Using SQL, Python, and Tableau, I examined revenue trends, margin performance, product mix, and promotion impact to identify the key drivers of growth, profitability, and operational efficiency.Below are the key insights from the analysis.

  • Stable growth: Revenue increased €187K (+4.4%) from 2024–2025, with margin tracking closely alongside sales.

  • Seasonal demand: Sales peak between May–October, with strongest growth in late spring and summer.

  • Scale drives performance: Top pharmacies generate more revenue through volume, while margin % remains consistent across locations.

  • Promotion inefficiency: Discounts reduce margin and generate limited volume uplift, suggesting current promotions are under-optimized.

This project analyzes consumer browsing behavior and purchase intent for an online clothing e-shop.Using SQL and Tableau, I examined user interaction data to identify traffic patterns, product demand, geographic engagement, and conversion funnel behavior. The goal is to understand how users move from casual browsing to high purchase intent and uncover opportunities to improve conversion.Below are the key insights from the analysis.

  • Traffic concentration: Poland generates the largest share of site traffic, reflecting the store’s primary market.

  • High-intent engagement: Lithuania and the Czech Republic show strong purchase intent relative to traffic volume, indicating high-value markets.

  • Product demand: Pants are the most viewed category, while Product B4 (Skirt) receives the highest high-intent views.

  • Funnel drop-off: Only ~10% of users become deep browsers and ~3% reach high purchase intent, highlighting significant conversion opportunities.

This project analyzes academic performance data for 2,392 high school students to identify the key behavioral and environmental factors influencing GPA and overall grade outcomes.Using Excel and interactive dashboards, I explored how study habits, parental support, and extracurricular participation relate to student performance. The goal is to uncover data-driven insights that support academic interventions and student success strategies.Below are the key insights from the analysis.

  • Widespread underperformance: Over 50% of students receive failing grades, pulling overall GPA averages downward.

  • Study habits matter: Higher weekly study time consistently correlates with higher GPA, making it the strongest academic driver.

  • Attendance impact: Student absences sharply reduce GPA, highlighting attendance as a key risk indicator.

  • Support & engagement: Parental support and extracurricular participation are both associated with higher student GPAs.

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