CSV

〽️ The eLxr Metrics project is designed to provide insights into the website performance and package distribution metrics. It tracks key indicators such as website view count and download statistics for binary packages📦, presenting the data in visually informative charts📊📈.

A personal project to advance my career in data science as a whole.

PaveDB — A lightweight, pluggable vector search microservice with built-in document ingestion and deep observability.

Upload → chunk → index (with metadata) → search via REST and CLI, scoped by multi-tenant collections.

Website: https://pavedb.org

Static API security scanner — detects undocumented and unauthenticated Express.js routes before they reach production

Keep logs of Lichess Puzzle of The Day (daily puzzle).

Offline PDF to XLSX/CSV/JSON converter for Yandex Bank statements (deposit Сейв + card account). Конвертер банковских выписок Яндекс Банка из PDF в Excel — всё локально.

Offline PDF to XLSX/CSV/JSON converter for Ozon Bank (ОЗОН Банк) statements. Конвертер банковских выписок Озон Банка из PDF в Excel — всё локально.

🦊 AI secretary for Telegram Business — auto-replies, Notion tasks, Google Calendar, voice transcription, photo analysis

A small PHP extension to add/improve the handling of CSV strings.

Analysis of Kilter Board data, along with predictive models for V-grades based on holds and angle.

Analysis of Tension Board 2 data, along with predictive models for V-grades based on holds and angle.

Lightweight desktop tool for converting and validating tabular datasets into efficient Parquet format.

GitLab pages content: several projects that I contribute/d to

also available at eUgEntOptIc44.codeberg.page and eUgEntOptIc44.github.io

Download Yahoo Finance end-of-day prices and export them to a Quicken-compatible CSV.

Curated airport traffic rankings: final 2025 passenger, international, cargo and aircraft-movement data, historical No. 1 airport titles, and preliminary H1 2026 international traffic.

CASE STUDY: Netflix User Engagement & Revenue Analysis Project Overview

A comprehensive data analysis project analyzing Netflix-style streaming platform data using SQL for data extraction and Power BI for visualization. The project uncovers key insights about user behavior, content performance, and revenue trends.

PROBLEM STATEMENT

Business Challenge User Engagement: Content Performance Revenue Analysis: User Behavior:

SOLUTION APPROACH

Data Collection & Structure SQL Implementation Power BI Dashboard

KEY INSIGHTS DISCOVERED

Revenue Performance Total Revenue: $246.81 Highest Month: October 2024 ($136.89) Growth: 251% increase from September to October Best Payment Method: Credit Card (45% of revenue)

User Engagement Active Users: 10 users (100% engagement) Average Engagement Score: 52.5 Top User: Alex (Engagement Score: 59) Most Watched Genre: Sci-Fi (5 views)

Content Performance Top Movie: Multiple titles with 2+ views Best Genre: Sci-Fi and Drama (highest ratings) Device Preference: TV and Mobile (40% each) Average Completion Rate: 85.4%

Customer Insights Premium Users: 4 users (40%) Average Lifetime Value: $24.68 Top Reviewer: Multiple users with 3 reviews each Geographic Distribution: 5 countries represented

A business analytics project focused on understanding customer subscription journeys, identifying churn patterns, analyzing user engagement, and building an interactive Power BI dashboard with actionable insights.