Northwind Intelligence
Creator Profile
Professional background, achievements, and the complete project report.
Otabek Jurabekov
PDP University - Group 24-303
Created by Otabek Jurabekov
About the Developer
I'm Otabek Jurabekov, a student at PDP University (Group 24-303) and a professional competitive programmer and mathematician. I actively combine strong theoretical foundations with real-world engineering, focusing on building scalable backend systems and solving complex algorithmic problems.
I am an IOI 2023 (Hungary) participant, with extensive experience in international mathematics and informatics Olympiads. Over the years, competitive programming shaped my way of thinking - precision, performance, and correctness always come first.
Currently, I work as a Back-End Developer at Asaxiy.uz, where I build and maintain high-load backend services, and as a Laravel Back-End Developer at Revolution Group, contributing to production-grade systems with real users and real constraints.
I have solved 1400+ algorithmic problems across platforms and hold an Expert-level competitive programming background, with deep experience in algorithms, data structures, and problem-solving under pressure. I'm not just focused on passing tests - I focus on writing clean, efficient, and maintainable code.
I aim to bridge competitive programming discipline with modern software engineering, building systems that are both mathematically sound and practically robust.
Key Achievements
- IOI 2023 (Hungary) participant
- 1400+ algorithmic problems solved
- Expert-level competitive programmer
- Back-End Developer at Asaxiy.uz
- Laravel Back-End Developer at Revolution Group
Connect & Profiles
Project Report (Web)
Project Overview
Northwind Pulse is a fully dockerized analytics platform built with Next.js, MySQL, and Adminer. It transforms the classic Northwind dataset into decision-ready insights with KPI cards, trend charts, and deep operational dashboards.
Data Model & Preparation
The analysis joins SalesOrder, OrderDetail, Product, Category, Customer, Employee, Supplier, and Shipper tables. The pipeline cleans missing values, normalizes dates, and aggregates metrics such as revenue, order volume, and shipping performance.
Methods & Techniques
The dashboard applies descriptive analytics, time-series trends, ranking, and segmentation. Metrics are built using SUM, AVG, COUNT, and grouped comparisons to quantify revenue drivers and operational efficiency.
Visualization Coverage
Reports include revenue momentum, category share, shipping geography, discount impact, freight costs, inventory risk, supplier exposure, customer distribution, average order value, and employee performance by role and territory.
Governance & Ethics
The project documents data roles, compliance strategies, and ethical safeguards. Every visualization includes a toggle with its explanation and SQL to ensure transparency and reproducibility.
Deployment & Access
The live deployment runs on Ubuntu with Nginx reverse proxy and SSL. The production site is available at https://bigdata-assignment.ilmora.uz.