Introduction:
This course dives deep into MongoDB, a powerful NoSQL database built for storing and managing document-oriented data. We'll start at the beginning, exploring MongoDB's core concepts and its evolution as a leading database solution. Then, we'll get hands-on, guiding you through installation, essential CRUD operations (Create, Read, Update, Delete), and crafting effective queries to retrieve your data.
As you progress, we'll tackle database administration, application integration, and advanced topics like performance optimization, data modeling best practices, and robust security measures. Troubleshooting techniques and real-world use cases will equip you to confidently leverage MongoDB in your own projects.
By the end, you'll be a MongoDB pro, ready to tackle various data storage and management challenges!
Course Outline:
| Module | Title | Sections |
|---|---|---|
| 1 | Introduction to MongoDB | ◦ Understanding NoSQL databases ◦ Comparison with Relational Databases ◦ MongoDB History ◦ MongoDB Evolution ◦ Use Cases and Applications of MongoDB ◦ Benefits and Limitations of MongoDB |
| 2 | Getting Started with MongoDB | ◦ Installation and Setup of MongoDB ◦ Introduction to MongoDB Shell ◦ Basic CRUD Operations ◦ Data Modelling Concepts ◦ Understanding BSON and Document Structure |
| 3 | Querying MongoDB | ◦ Query Operators and Expressions ◦ Projection and Aggregation Framework ◦ Indexing and Query Performance Optimization ◦ Text Search and Geospatial Queries ◦ Arrays and Nested Documents |
| 4 | Data Administration in MongoDB | ◦ Managing Databases and Collections ◦ Backup and Restore Strategies ◦ Replication for High Availability ◦ Sharding and Horizontal Scalability ◦ Best Practices For Security and Authentication |
| 5 | Advanced MongoDB Features | ◦ Introduction to MongoDB Atlas ◦ Working with MongoDB Compass ◦ Time-Series Data Management ◦ Change Streams and Real-Time Data Processing ◦ GridFS for Storing Large Files |
| 6 | Integrating MongoDB with Applications | ◦ MongoDB Drivers and Client Libraries ◦ Connecting MongoDB with Node.js, Python, and Java ◦ Building RESTful APIs with MongoDB ◦ Using MongoDB with Frameworks like Express.js ◦ Case Studies of MongoDB Integration in Real-world Applications |
| 7 | Performance Tuning and Optimization | ◦ MongoDB Performance Metrics ◦ Identifying Bottlenecks and Performance Issues ◦ Query Profiling and Optimization Techniques ◦ Hardware Sizing and Capacity Planning ◦ Best Practices for Maintaining Optimal Performance |
| 8 | Data 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 |
| 9 | Security and Compliance | ◦ Authentication Methods in MongoDB ◦ Role-Based Access Control (RBAC) ◦ Encryption at Rest and in Transit ◦ Auditing and Compliance Considerations ◦ Securing MongoDB Deployments in Production |
| 10 | Troubleshooting and Maintenance | ◦ Common Issues and Error Handling ◦ Diagnosing and Resolving Replication Lag ◦ Failover Handling and Disaster Recovery ◦ Upgrading MongoDB Versions Safely ◦ Community Support and Resources for Troubleshooting |
| 11 | Practical Applications and Use Cases | ◦ Industry-specific Applications of MongoDB ◦ Real-world Examples of MongoDB Implementations ◦ Designing Scalable and Flexible Data Architectures ◦ Emerging Trends and Innovation ideas with MongoDB |
- 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 consists 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 Optimisation [10]
- Data Modelling and Schema Design [10]
- Security and Compliance [10]
- Troubleshooting and maintenance [5]
- Practical Applications and Use Cases [10]
