Big Data Analysis with MongoDB

Lecture Series

Big Data Analysis with MongoDB

A comprehensive, hands-on tutorial series covering environment setup, MongoDB fundamentals, and advanced data analysis techniques with real-world large-scale datasets.

Environment Setup

Complete Environment Setup

Install VSCode, Docker, MongoDB, and all required extensions. Set up your development environment from scratch with step-by-step instructions for Ubuntu/Debian and Fedora/RHEL.

30-45 min Beginner 7 steps

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Fundamentals

MongoDB Fundamentals

Learn CRUD operations, querying with comparison & logical operators, sorting, projection, and aggregation pipelines. Work with the Sample Supplies dataset (5000 records).

60-90 min Intermediate 7 exercises

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Advanced

Advanced MongoDB with Real-World Data

Master nested documents, arrays, embedding vs referencing, $lookup joins, and multi-stage aggregation pipelines. Analyze the Olist E-Commerce (100K+ orders) and Amazon M2 datasets.

90-120 min Advanced 10 exercises

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Sharding & Distributed MongoDB

Build a real sharded cluster in Docker — config servers, two shards, and a mongos router. Shard the Olist orders collection, watch documents distribute and rebalance across shards, and learn how shard keys route queries.

60-90 min Ultra Advanced 5 exercises

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Prerequisites

A computer running Ubuntu/Debian or Fedora/RHEL Linux
Internet connection for downloading packages
Basic familiarity with the terminal / command line
Tutorials should be completed in order (1 → 2 → 3 → 4)

Datasets Used

Sample Supplies — 5000 sales transactions (Tutorial 2)
Olist Brazilian E-Commerce — 100K+ anonymized orders with customers, products, payments, reviews (Tutorial 3)
Amazon M2 Big Data — Millions of shopping sessions across six locales (Tutorial 3)