Vitalii Korolkov
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Offer work
Kharkiv,
Ukraine
3 days 15 hours back
available for hire
age 35 years
on the service 2 months 28 days
Rating
Successful projects
Average rating
Language proficiency level
Українська: fluent
English: pre-intermediate
Skills and abilities
Programming
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Data Parsing
from 11 USD for project
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Databases & SQL
from 11 USD for project
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Python
from 11 USD for project
Services
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Data Processing
from 11 USD for project
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Enterprise Resource Planning (ERP)
from 11 USD for project
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Information Gathering
from 11 USD for project
Portfolio
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22 USD Tableau Project: Revenue Dashboard 2022–2023 (ARPPU, MRR, cohorts)
Developed an interactive dashboard in Tableau for analyzing revenue dynamics, ARPPU trends, and user cohorts. Integrated payment data, calculated monthly recurring revenue (MRR), user retention, and percentage growth. Visualized key business metrics to identify revenue fluctuations and improve decision-making.
Key results:
• Built visualizations of ARPPU and MRR to track revenue growth month by month
• Created cohort analysis to assess user retention and recurring revenue
… • Increased reporting speed and data transparency for business analysis.
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13 USD Delivery Time Analysis — Superstore
Analyzed the delivery efficiency across the states of the USA using the Superstore dataset to identify patterns in delivery time and operational efficiency. Calculated the delivery duration — from the moment of order to shipment — and visualized:
• Average number of delivery days by delivery types (e.g., First Class, Standard Class)
• Distribution of orders by number of delivery days
• Average delivery time by states on a geographical map with gradient visualization
… Key insights:
• Standard Class delivery takes the most time (on average 4–5 days), while Same Day is completed within 1 day
• Central states of the USA demonstrate a somewhat faster average delivery time
Result:
Created an interactive dashboard in Tableau with filters by order date, segment, and delivery type, allowing for flexible analysis of delivery efficiency and identification of bottlenecks.
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18 USD E-commerce Funnel Analysis | GA4 + BigQuery + Tableau
Databases & SQL
I created a comprehensive analytical e-commerce funnel dashboard using a sample GA4 data.
Project goal:
To help the marketing manager understand how users move through the purchase funnel and identify at which stage the largest loss of conversions occurs.
What I did:
… • Retrieved and transformed GA4 data in BigQuery using SQL (CTE, JOIN)
• Built a session-level dataset with key funnel stages
• Developed an interactive dashboard in Tableau Public
• Implemented filters by date, traffic source, campaign, device, OS, and language
• Visualized the entire funnel — from the start of the session to the purchase
Key insights:
• The largest user drop-off occurs at the add-to-cart stage
• Not all traffic sources that bring sessions generate purchases
• Funnel effectiveness varies significantly depending on the traffic channel and device type
Technology stack:
SQL (BigQuery), GA4, Tableau Public