Objective
MongoDB is an open-source NoSQL document database that provides high performance, high availability, and automatic scaling. MongoDB provides high performance data persistence such as support for embedded data models reduces I/O activity on database system and it has indexes which support faster queries and can include keys from embedded documents and arrays.

An Overview of Big data

• What is Big Data.
• Different formats of data
• Distributed and Parallel processing of Big Data
• Different frameworks for handling Big Data
• Batch and Real Time Processing

An Overview of SQL Relational Databases

• The Role of the MySQL Database Server
• Databases, Tables, Rows and Columns
• Recap on Primary Keys and Foreign Keys Explained

Understanding of NoSQL Non-Relational Databases

• Introduction to NoSQL databases
• Landscape of NoSQL
• CAP Theorem and Eventual consistency 
• Batch Time Processing v/s Real Time processing
• Difference between NoSQL and SQL databases
• Introduction to different types of NoSQL databases
• Key – value
• Columnar
• Document
• Graph based

Introduction to NoSQL MongoDB Document Databases

• Introduction to MongoDB databases
• Installation of MongoDB 3.4.9 on Linux environment RHEL (6 or 7) 64 bit
• MongoDB – deployment 
• Mongo Shell
• Databases and Collections

CRUD operations

• Views
• Documents
• Data Import from JSON format
• Inserting documents
• Query documents with conditions
• Sort and Limit operations
• Updating documents
• Upsert operations
• Data export

Indexes

• Creating Indexes
• Text Indexes and Search

Aggregation Framework

• Aggregation concepts
• Aggregation Pipelines
• Shell Methods
• Query Operators

Schema Design

• Schema Design concepts for MongoDB
• One to Many and Many to Many relationships
• Embedding documents

Replication and Sharding

• Understanding Replication
• Replica sets
• Concepts of Sharding
• Impact of Sharding on performance