MongoDB - Corporate Training

The objective of the MongoDB course is to equip participants with comprehensive knowledge and practical skills necessary to proficiently work with MongoDB across its entire ecosystem.
Upon completing the MongoDB course, Participants will gain expertise in MongoDB's architecture, CRUD operations, indexing, aggregation, data modeling, administration (including replication, sharding, monitoring, and backup), security measures, advanced topics such as integration with big data technologies and cloud deployment, as well as real-world application through case studies and project work.
The course aims to prepare participants to effectively design, deploy, manage, and optimize MongoDB databases and applications in diverse operational environments.

Overview of MongoDB (1 hour)
– Understanding NoSQL databases
– Introduction to MongoDB
– Key features and benefits of MongoDB
MongoDB Architecture (2 hours)
– Core concepts: Collections and Documents
– Data types in MongoDB
– MongoDB deployment options (standalone, replica sets, sharded clusters)
– Introduction to BSON
Installation and Setup (2 hours)
– Installation of MongoDB on various platforms (Windows, macOS, Linux)
– Basic configuration and setup
– Overview of MongoDB tools (mongo shell, MongoDB Compass)
Hands-on Lab: Setting Up MongoDB (2 hours)
– Installing MongoDB
– Basic configuration and connectivity
– Creating and managing databases

Module 2: CRUD Operations

Basic CRUD Operations (2 hours)
– Creating databases and collections
– Inserting documents
– Querying documents
– Updating documents
– Deleting documents
Advanced Querying (3 hours)
– Query operators
– Projection
– Sorting and pagination
– Aggregation framework basics
Hands-on Lab: CRUD Operations (3 hours)
– Performing basic CRUD operations
– Querying with different operators
– Using aggregation framework for data analysis

Indexing (2 hours)
– Understanding indexing in MongoDB
– Creating and managing indexes
– Types of indexes (single field, compound, multi-key, text, geospatial)
– Indexing strategies and performance considerations
Aggregation Framework (3 hours)
– Introduction to aggregation framework
– Stages in aggregation pipelines
– Common aggregation operations (match, group, project, unwind)
– Aggregation framework use cases
Hands-on Lab: Indexing and Aggregation (3 hours)
– Creating and managing different types of indexes
– Building aggregation pipelines
– Analyzing data with aggregation framework

Module 4: Data Modeling

Schema Design (3 hours)
– Data modeling principles in MongoDB
– Embedded documents vs. references
– One-to-One, One-to-Many, Many-to-Many relationships
– Schema design best practices
Schema Evolution (2 hours)
– Handling schema changes in MongoDB
– Strategies for schema migration
– Tools for schema management
Hands-on Lab: Data Modeling (3 hours)
– Designing schemas for different use cases
– Implementing relationships between documents
– Managing schema changes

Module 5: Administration

Replication (3 hours)
– Introduction to replication in MongoDB
– Setting up replica sets
– Failover and recovery
– Read and write concerns in replication
Sharding (3 hours)
– Introduction to sharding
– Sharding components (shard, mongos, config server)
– Setting up a sharded cluster
– Balancing and migrating chunks
Monitoring and Performance Tuning (3 hours)
– Monitoring MongoDB instances
– Performance tuning strategies
– Tools for monitoring and optimization (Profiler, Cloud Manager, Ops Manager)
Backup and Recovery (2 hours)
– Backup strategies and tools (mongodump, mongorestore)
– Point-in-time recovery
– Automating backups
Hands-on Lab: Administration (4 hours)
– Setting up and managing replica sets
– Configuring and managing sharded clusters
– Performance tuning and monitoring exercises
– Implementing backup and recovery strategies

Module 6: Security

Authentication and Authorization (3 hours)
– Enabling authentication in MongoDB
– User management and roles
– Role-based access control (RBAC)
Encryption and Auditing (2 hours)
– Data encryption at rest and in transit
– Configuring TLS/SSL
– Auditing database activities
Hands-on Lab: Security (2 hours)
– Implementing authentication and authorization
– Configuring encryption
– Setting up auditing

Module 7: Advanced Topics

MongoDB with Big Data Technologies (3 hours)
– Integration with Hadoop and Spark
– Using MongoDB as a data source for big data processing
MongoDB in the Cloud (2 hours)
– Introduction to MongoDB Atlas
– Deploying MongoDB on cloud platforms (AWS, Azure, GCP)
– Cloud-native features and considerations
Hands-on Lab: Advanced Topics (3 hours)
– Integrating MongoDB with big data tools
– Deploying and managing MongoDB in the cloud

Case Studies (2 hours)
– Real-world applications of MongoDB
– Customer success stories and use cases
Project Work (5 hours)
– Design and implement a solution using MongoDB
– Present and discuss project outcomes