As data engineering increasingly demands handling diverse, large-scale, and high-velocity data, mastering NoSQL databases becomes crucial. This Advanced NoSQL for Data Engineers (MongoDB, Cassandra, etc.) training course equips participants with practical and in-depth expertise to design, optimize, and manage distributed NoSQL systems used in modern big data pipelines. Through a hands-on approach, participants will explore schema design, indexing, querying, replication, sharding, and performance tuning with leading NoSQL platforms such as MongoDB, Apache Cassandra, Redis, and others. Ideal for professionals building real-time analytics platforms, microservices backends, or IoT-scale infrastructure, this course ensures engineers are fully capable of leveraging NoSQL technologies for scalability, flexibility, and high availability.

Duration: 10 Days

Target Audience

• Data Engineers building scalable data infrastructure
• Database Administrators transitioning to NoSQL platforms
• Backend Developers implementing NoSQL-driven applications
• DevOps Engineers managing distributed systems
• Cloud Engineers deploying NoSQL services at scale
• Data Architects designing flexible and performant schemas
• ETL Developers optimizing data ingestion into NoSQL systems
• Full-Stack Developers integrating NoSQL into backend APIs

Course Objectives

• Understand the core principles of NoSQL database types and architectures
• Gain deep hands-on experience with MongoDB and Apache Cassandra
• Design high-performance NoSQL schemas for real-world applications
• Implement advanced indexing, sharding, and replication strategies
• Integrate NoSQL databases with modern data pipelines
• Optimize NoSQL query performance and throughput
• Ensure data consistency and availability across distributed clusters
• Monitor and maintain large-scale NoSQL infrastructure
• Secure NoSQL deployments with proper access control and encryption
• Compare and evaluate NoSQL options for specific business needs
• Build resilient, cloud-native NoSQL-powered systems

Module 1: Introduction to NoSQL Databases

• Understanding the evolution from relational to NoSQL databases
• Classification: key-value, document, wide-column, and graph databases
• Use cases and advantages of NoSQL over traditional RDBMS
• CAP theorem and its implications on NoSQL systems
• Overview of popular NoSQL platforms and ecosystems

Module 2: MongoDB Essentials

• Document data model and BSON structure
• CRUD operations with MongoDB shell and drivers
• Indexing strategies for performance optimization
• Schema design best practices for flexible structures
• Aggregation framework and pipeline patterns

Module 3: Advanced MongoDB Operations

• Replication and replica set configuration
• Sharding and horizontal scaling techniques
• Transactions and ACID compliance in MongoDB
• Backup, restore, and disaster recovery planning
• Performance tuning and profiling queries

Module 4: Apache Cassandra Basics

• Introduction to wide-column data models
• Understanding Cassandra architecture and write path
• Keyspaces, tables, and CQL (Cassandra Query Language)
• Partitions and clustering for distributed data
• Data modeling patterns for time series and events

Module 5: Cassandra Data Management and Tuning

• Replication strategies and consistency levels
• Read/write performance optimization
• Compaction, caching, and garbage collection settings
• Using nodetool and cqlsh for cluster management
• Monitoring metrics and alerts in production

Module 6: Redis and In-Memory NoSQL

• Key-value store concepts with Redis
• Use cases: caching, pub/sub, real-time counters
• Data structures: sets, lists, sorted sets, hashes
• Persistence options and memory optimization
• Redis Cluster and Sentinel configuration

Module 7: Schema Design Principles in NoSQL

• Designing for reads vs writes in NoSQL systems
• Denormalization and embedded document strategies
• Modeling one-to-many and many-to-many relationships
• Choosing partition keys and avoiding hotspots
• Trade-offs between flexibility and consistency

Module 8: Query Optimization in NoSQL Systems

• Indexing techniques and query planners
• Aggregation tuning and pipeline optimization
• Query profiling tools in MongoDB and Cassandra
• Latency reduction and throughput scaling
• Identifying and resolving anti-patterns

Module 9: NoSQL Security and Access Control

• Authentication and role-based access in MongoDB
• Secure client connections using TLS/SSL
• Auditing and activity logging
• Data encryption at rest and in transit
• Security hardening of NoSQL clusters

Module 10: NoSQL Backup, Restore, and High Availability

• Snapshot-based backup strategies
• Point-in-time recovery techniques
• Cluster failover and leader election
• Data migration across environments
• Ensuring uptime with distributed replication

Module 11: Integrating NoSQL with Data Pipelines

• Connecting NoSQL systems with Apache Kafka and Spark
• Streaming data ingestion from microservices
• ETL workflows with NoSQL as sink or source
• Data enrichment and transformation patterns
• Real-time analytics architecture

Module 12: Monitoring and Observability for NoSQL

• Prometheus and Grafana for MongoDB/Cassandra metrics
• Query performance dashboards and latency tracking
• Disk I/O, memory, and CPU usage monitoring
• Alerting strategies for cluster health
• Log aggregation and analysis

Module 13: Deploying NoSQL Databases in the Cloud

• Managed services (MongoDB Atlas, Amazon Keyspaces)
• Infrastructure as Code for provisioning clusters
• Auto-scaling and load balancing
• Cost optimization strategies in cloud environments
• Multi-region replication and latency considerations

Module 14: Comparing NoSQL Options and Use Cases

• Benchmarking MongoDB vs Cassandra vs Redis
• Selecting the right NoSQL database by workload
• Hybrid architectures with SQL + NoSQL
• Polyglot persistence strategies
• Business case evaluation

Module 15: Capstone Project: Building a NoSQL-Driven Data Platform

• Designing a high-throughput document and key-value data store
• Implementing schema, indexing, and access controls
• Integrating the system with real-time ingestion pipelines
• Monitoring, securing, and deploying the solution
• Presenting project outcomes and scalability plans

Training Approach

This course will be delivered by our skilled trainers who have vast knowledge and experience as expert professionals in the fields. The course is taught in English and through a mix of theory, practical activities, group discussion and case studies. Course manuals and additional training materials will be provided to the participants upon completion of the training.

Tailor-Made Course

This course can also be tailor-made to meet organization requirement. For further inquiries, please contact us on: Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Training Venue

The training will be held at our Skills for Africa Training Institute Training Centre. We also offer training for a group at requested location all over the world. The course fee covers the course tuition, training materials, two break refreshments, and buffet lunch.

Visa application, travel expenses, airport transfers, dinners, accommodation, insurance, and other personal expenses are catered by the participant

Certification

Participants will be issued with Skills for Africa Training Institute certificate upon completion of this course.

Airport Pickup and Accommodation

Airport pickup and accommodation is arranged upon request. For booking contact our Training Coordinator through Email: info@skillsforafrica.org, training@skillsforafrica.org Tel: +254 702 249 449

Terms of Payment: Unless otherwise agreed between the two parties’ payment of the course fee should be done 7 working days before commencement of the training.