The Complete Guide to NoSQL Databases with MongoDB

NoSQL MongoDB Advanced Intermediate Course

Introduction:

This specialized course is designed to delve into NoSQL databases, offering insights into various methods for storing and managing data in a document format. Throughout this program, participants will explore MongoDB from its fundamentals to advanced features and practical applications. Starting with an introduction to NoSQL databases and MongoDB’s evolution, learners will progress through installation, basic CRUD operations, querying, administration, and integration with applications. Advanced topics include performance optimization, data modelling, security, troubleshooting, and real-world use cases. By the end of this course, participants will have the skills to leverage MongoDB effectively in various projects and scenarios. Let’s dive in and unlock the power of MongoDB together!

Course Outline:

ModuleTitleSections
1Getting Started with NoSQL Databases/MongoDB◦ Understanding NoSQL databases
◦ Comparison with Relational Databases
◦ Structured Data vs Unstructured Data
◦ Use Cases and Applications of MongoDB
◦ MongoDB Atlas Hosting Installation
◦ MongoDB Installation and Configuration
◦ Introduction to MongoDB Shell
◦ Introduction and Setting Up of MongoDB Compass
◦ MongoDB Compass Navigation
2Database Foundation Concepts◦ Data Types and Requirements
◦ Understanding BSON/JSON and Schema Structure
◦ MongoDB Field and Value Pair Structure
3MongoDB Query, Data Warehousing and Aggregation◦ Query Operators and Expressions
◦ Using Create, Read, Update and Delete (CRUD) operations
◦ Projection
◦ Indexing and Query Performance Optimisation
◦ Text Search and Geospatial Queries
◦ Arrays and Nested Documents
◦ Querying From Multiple Collections or Databases
◦ Data Organising and Database Warehousing
◦ Aggregation Framework
4MongoDB Performance Statistics and Indicators◦ MongoDB Performance Metrics
◦ Tools to Extract Performance Metrics
◦ Performance Metrics Analysing
◦ Query Profiling and Optimisation Techniques
◦ Hardware Sizing and Capacity Planning
◦ Best Practices for Maintaining Optimal Performance
5Data Modelling and Schema Design◦ Principles of Schema Design
◦ Normalization vs. Denormalization
◦ Designing Read and Write Operations
◦ Modelling Relationships and Embedding Documents
◦ Schema Design Patterns and Anti-patterns
◦ Database Compartmentalizing
6Administration in MongoDB◦ Managing Databases and Collections
◦ Users and Permission Handling
◦ Role Based Access Control
◦ Backup, Restore and Reporting Strategies
◦ Database Replication for High Availability
◦ Database Sharding and Horizontal Scalability
◦ Best Practices For Security and Authentication
7Database Maintenance◦ Time-Series Data Management
◦ Change Streams and Real-Time Data Processing
◦ GridFS for Storing Large Files
◦ Common Issues and Error Handling
◦ Failover Handling and Disaster Recovery
◦ Upgrading MongoDB Versions Safely
◦ Community Support and Resources for Troubleshooting

  • 15 hours
  • 2 Day Course
  • Classroom-based, Instructor-led Training

Assessment Format:

A competency-based assessment will be in the form of written examination, primarily consisting of 30 multiple choice questions spanning various aspects as covered in the program. 

Each participant will be assessed individually on the last day of the training for their understanding of the subject matter and ability to evaluate, choose and apply them in specific context and also the ability to identify and manage risks. The assessment focuses on higher levels of learning in Bloom’s taxonomy: Application, Analysis, Synthesis and Evaluation.

The objective of the certification examination is to evaluate the knowledge + skills acquired by the participants during the course on Big Data. 

Exam Preparation:

The weightage in key topics of the course as follows:

  • Introduction to MongoDB[5]
  • Getting Started With MongoDB [10]
  • Querying with MongoDB [10]
  • Data Administration With MongoDB [10]
  • Advance MongoDB Features [10]
  • Integrating MongoDB with Applications  [10]
  • Performance Tuning and Optimization [10]
  • Data Modelling and Schema Design [10]
  • Security and Compliance [10]
  • Troubleshooting and maintenance [5]
  • Practical Applications and Use Cases [10]