Real-time Data Pipelines Training Course: Build Live Data Systems

Introduction

Transform your data handling capabilities with our Real-Time Data Pipelines Training Course. This program is designed to equip you with the essential skills to design and implement systems for real-time data processing, enabling you to build robust and scalable data pipelines that deliver immediate insights. In today's fast-paced data landscape, mastering real-time data processing is crucial for organizations seeking to leverage live data for informed decision-making. Our real-time data pipelines training course offers hands-on experience and expert guidance, empowering you to build systems that capture, process, and analyze data streams with minimal latency.

This build live data systems training delves into the core concepts of real-time data processing, covering topics such as stream processing, message queues, and distributed systems. You'll gain expertise in using industry-standard techniques to design and implement systems for real-time data processing, meeting the demands of modern data-driven organizations. Whether you're a data engineer, software developer, or data architect, this Real-Time Data Pipelines course will empower you to design and implement high-performance real-time data solutions.

Target Audience:

• Data Engineers
• Software Developers
• Data Architects
• Systems Engineers
• DevOps Engineers
• Backend Developers
• Anyone needing real-time data processing skills

Course Objectives:

• Understand the fundamentals of real-time data pipelines.
• Master stream processing concepts and technologies.
• Utilize message queues and distributed systems for data ingestion.
• Implement data transformation and aggregation in real-time.
• Design and build scalable real-time data processing systems.
• Optimize data pipelines for low latency and high throughput.
• Troubleshoot and address common issues in real-time systems.
• Implement data serialization and schema management for streaming data.
• Integrate real-time data pipelines with various data storage and analytics platforms.
• Understand how to handle data consistency and fault tolerance in real-time systems.
• Explore advanced real-time data processing techniques (e.g., windowing, state management).
• Apply real world use cases for real-time data pipelines.
• Leverage real-time data processing tools and frameworks for efficient implementation.

Duration

10 Days

Course content

Module 1: Introduction to Real-Time Data Pipelines

• Fundamentals of real-time data pipelines.
• Overview of stream processing, message queues, and distributed systems.
• Setting up a real-time data processing development environment.
• Introduction to real-time data processing tools and frameworks.
• Best practices for real-time data pipelines.

Module 2: Stream Processing Concepts

• Mastering stream processing concepts and technologies.
• Understanding data streams, event processing, and windowing.
• Designing and building stream processing applications.
• Optimizing stream processing for low latency.
• Best practices for stream processing.

Module 3: Message Queues and Distributed Systems

• Utilizing message queues and distributed systems for data ingestion.
• Implementing message brokers (e.g., Kafka, RabbitMQ).
• Designing and building distributed data pipelines.
• Optimizing data ingestion for high throughput.
• Best practices for message queues.

Module 4: Data Transformation and Aggregation

• Implementing data transformation and aggregation in real-time.
• Utilizing stream processing libraries and frameworks.
• Designing and building data transformation workflows.
• Optimizing data aggregation for real-time analytics.
• Best practices for data transformation.

Module 5: Scalable Real-Time Systems

• Designing and building scalable real-time data processing systems.
• Utilizing distributed computing frameworks (e.g., Apache Flink, Apache Spark Streaming).
• Implementing data partitioning and parallel processing.
• Optimizing systems for scalability and performance.
• Best practices for scalable systems.

Module 6: Pipeline Optimization

• Optimizing data pipelines for low latency and high throughput.
• Utilizing performance tuning and monitoring tools.
• Implementing data buffering and caching strategies.
• Designing efficient data processing architectures.
• Best practices for pipeline optimization.

Module 7: Troubleshooting Real-Time Systems

• Debugging common issues in real-time systems.
• Analyzing system logs and error messages.
• Utilizing troubleshooting techniques for problem resolution.
• Resolving common data processing errors.
• Best practices for troubleshooting.

Module 8: Data Serialization and Schema Management

• Implementing data serialization and schema management for streaming data.
• Utilizing Avro, Protobuf, and JSON schema.
• Designing and building schema registries.
• Optimizing data serialization for performance.
• Best practices for data serialization.

Module 9: Integration with Data Platforms

• Integrating real-time data pipelines with various data storage and analytics platforms.
• Utilizing data streaming connectors and APIs.
• Implementing data integration with external databases and data lakes.
• Optimizing integration for data retrieval and analysis.
• Best practices for integration.

Module 10: Data Consistency and Fault Tolerance

• Understanding how to handle data consistency and fault tolerance in real-time systems.
• Utilizing data replication and checkpointing.
• Implementing fault-tolerant data pipelines.
• Designing robust data processing workflows.
• Best practices for consistency.

Module 11: Advanced Real-Time Techniques

• Exploring advanced real-time data processing techniques (windowing, state management).
• Utilizing windowing for time-based data aggregation.
• Implementing state management for complex event processing.
• Designing and building advanced real-time solutions.
• Optimizing advanced techniques for specific applications.
• Best practices for advanced techniques.

Module 12: Real-World Use Cases

• Implementing real-time data pipelines for IoT data processing.
• Utilizing real-time data for fraud detection and security monitoring.
• Implementing real-time data for log aggregation and analytics.
• Utilizing real-time data for financial transaction processing.
• Best practices for real-world applications.

Module 13: Real-Time Tools Implementation

• Utilizing real-time data processing tools and frameworks (Apache Flink, Kafka Streams).
• Implementing data pipelines with specific tools.
• Designing and building automated deployment workflows.
• Optimizing tool usage for efficient development.
• Best practices for tool implementation.

Module 14: Pipeline Monitoring and Logging

• Implementing pipeline monitoring and logging for real-time systems.
• Utilizing monitoring tools and metrics.
• Designing and building performance dashboards.
• Optimizing monitoring for real-time insights.
• Best practices for monitoring.

Module 15: Future Trends in Real-Time Data Processing

• Emerging trends in real-time data processing.
• Utilizing AI for real-time data analysis.
• Implementing real-time data mesh architectures.
• Best practices for future applications.

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.