Simple presentation about MongoDB and Big data analytics

1. MongoDB & Big Data
Analytics

2. What is MongoDB?
 MongoDB was first developed in 2007 by a company
called 10gen, which later change its name to MongoDB.
It was officially released to the public in 2009.
 MongoDB is a NoSQL database that stores data in
flexible, JSON-like documents.
 The goal was to create a modern database that could
handle the growing needs of web application.
 Especially those that needed to store large amounts of
unstructured or semi-structured data.

3. Key Features of MongoDB
 Document-Oriented: Stores data as collections of
documents.
 Flexible Schema: No need to predefine the structure
of the data.
 High Performance: Fast read/write operations.
 Scalable: Easily grows with big data.
 Powerful Query Language: Allows filtering,
aggregation, and full-text search.

4. MongoDB in Big Data Analytics
 Used to manage and analyze large datasets in real
time.
 Works well with data from sensors, logs, social
media, etc.
 Integrates with data visualization tools like MongoDB
Charts.
 Supports aggregation pipelines to process and
summarize data.

5. Dataset Overview
Dataset Name: KE April 2025 Data of SITE industrial
feeders (KE Outages)
Description:
This dataset contains information about power outages
from different feeders of SITE area. It includes:
 Outage types (like Feeder Trip, Incoming Trip, Load
Management)
 Fault types (Shutdown, Fault, Operational, etc.)
 Dates and counts of outages

6. MongoDB Chart Visualization

7. MongoDB Chart Visualization
What You See in the Dashboard:
 Total Outages: Shows total number of outage events.
 Outages Categories: Bar chart showing types of
outages.
 Fault Categories: Pie chart showing cause of outages.
 Outages Trend: Line graph showing outages over
time.
 Feeder Wise Outages: Feeder-wise bar chart of
outages.

8. Explanation of Charts
 Bar Chart: Most outages are due to “Feeder Trip.”
 Pie Chart: Most faults are due to general “Fault”
category.
 Trend Line: Shows a steady increase in outages over
days in April 2025.
 Feeder Chart: Identifies top feeders experiencing
frequent outages.

9. Benefits of Using MongoDB
 Handles high-volume, fast-changing data
 Easy integration with analytics tools
 Reduces development time with flexible schema
 Scalable and fault-tolerant

10. Summary
 MongoDB is a powerful, flexible tool for managing
big data.
 Using MongoDB Charts, we can quickly build
interactive visualizations.
 It's a great choice for real-time analytics in industries
like energy, healthcare, IoT, and more.

11. Thank You
 Any Questions?