PyMongo Case Study - Aggregating Customer Data of a Bank

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PyMongo Case Study - Aggregating Customer Data of a Bank

This course is part of Python NoSQL Data Engineering with MongoDB Specialization

Instructor: EDUCBA

Included with

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2 modules

Gain insight into a topic and learn the fundamentals.

31 reviews

Intermediate level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

2 modules

Gain insight into a topic and learn the fundamentals.

31 reviews

Intermediate level

Recommended experience

5 hours to complete

Flexible schedule

Learn at your own pace

Skills you'll gain

Tools you'll learn

MongoDB

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

6 assignments

Taught in English

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This course is part of the Python NoSQL Data Engineering with MongoDB Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

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There are 2 modules in this course

This practical, hands-on course empowers learners to apply the PyMongo library in building robust data solutions tailored to banking environments. Through a structured case study, participants will construct a modular Python-MongoDB integration that loads, segments, and analyzes real-world customer data.

In Module 1, learners will set up the project environment, connect to MongoDB using PyMongo, and prepare structured logging and file ingestion mechanisms. In Module 2, they will design advanced aggregation pipelines to segment customer records based on banking logic and generate insights through data grouping, transformation, and analysis. By the end of the course, learners will have the skills to implement end-to-end data workflows in MongoDB using PyMongo—ranging from raw file loading to actionable data summarization—preparing them for real-world data engineering and analytics tasks in the financial domain.

This module introduces learners to the foundational components of the PyMongo-based banking data project. It begins with project setup, including environment preparation, structured logging, and modular programming practices. Learners will then connect to MongoDB using PyMongo, fetch and load CSV-based customer data, and apply essential data validation techniques. The module emphasizes practical integration between Python and MongoDB to facilitate structured data ingestion and preparation for aggregation.

What's included

8 videos3 assignments

8 videosTotal 65 minutes

Introduction to Project8 minutes
Mongo Connection5 minutes
Creating The Project part 18 minutes
Creating The Project part 210 minutes
Creating The Project part 35 minutes
Fetching Mongo Collection12 minutes
File Load to Mongo10 minutes
File Load to Mongo Continue7 minutes

3 assignmentsTotal 50 minutes

Project Setup and MongoDB Connection10 minutes
Working with MongoDB Data Sources10 minutes
Graded - Building the MongoDB-Python Integration30 minutes

This module focuses on using MongoDB's powerful aggregation framework to segment and analyze customer data. Learners will begin by defining and structuring aggregation pipelines to filter, group, and transform raw banking data. They will then segment this data into logical collections based on business rules and perform advanced operations using stages such as $match, $group, $project, and $sort. By the end of this module, learners will have practical experience in converting unstructured datasets into meaningful summaries for decision-making and reporting.

What's included

6 videos3 assignments

6 videosTotal 49 minutes

Defining Aggregation Pipelines10 minutes
Segmenting Collections12 minutes
Segmenting Collections Continue7 minutes
Aggregation Data Part 17 minutes
Aggregation Data Part 27 minutes
Aggregation Data Part 36 minutes

3 assignmentsTotal 50 minutes

Designing and Executing Aggregation Pipelines10 minutes
Final Aggregation & Data Analysis10 minutes
Graded - Data Aggregation and Customer Segmentation30 minutes

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Instructor

Instructor ratings

(7 ratings)

EDUCBA

1,291 Courses294,073 learners

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EDUCBA

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Reviewed on Oct 9, 2025

Insightful and practical case study demonstrating effective use of PyMongo for real-world banking data aggregation.

Reviewed on Oct 23, 2025

Project is well-structured, easy to follow, and showcases real-world applications of data analytics using Python and MongoDB integration.

Reviewed on Dec 13, 2025

Overall, it’s a good course for learners who want practical exposure to MongoDB aggregations using Python in a real-world context.

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