MongoDB and Big data Analytics Simple.pptx
- 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
- 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?