Data Engineering & Devops Practices Training Course: Devops Data Pipelines

Introduction

Streamline your data operations with our Data Engineering and DevOps Practices Training Course. This program is designed to equip you with the essential skills to combine DevOps practices with data engineering, enabling you to build and deploy data pipelines with increased speed and reliability. In today's fast-paced data landscape, mastering DevOps for data engineering is crucial for organizations seeking to automate and optimize their data workflows. Our DevOps data engineering training course offers hands-on experience and expert guidance, empowering you to integrate DevOps principles into your data engineering projects.

This DevOps data pipelines training delves into the core concepts of DevOps applied to data engineering, covering topics such as continuous integration, continuous delivery, and infrastructure as code. You'll gain expertise in using industry-standard tools and techniques to combine DevOps practices with data engineering, meeting the demands of modern data-driven environments. Whether you're a data engineer, DevOps engineer, or cloud architect, this Data Engineering and DevOps Practices course will empower you to build and maintain efficient and scalable data systems.

Target Audience:

• Data Engineers
• DevOps Engineers
• Cloud Architects
• Data Architects
• Systems Administrators
• Software Developers
• Anyone needing DevOps data engineering skills

Course Objectives:

• Understand the fundamentals of data engineering and DevOps practices.
• Master continuous integration and continuous delivery (CI/CD) for data pipelines.
• Utilize infrastructure as code (IaC) for data infrastructure management.
• Implement automated testing and validation for data engineering workflows.
• Design and build efficient data pipeline deployment strategies.
• Optimize data engineering workflows for automation and scalability.
• Troubleshoot and address common issues in DevOps data implementations.
• Implement data governance and security in DevOps data environments.
• Integrate DevOps tools and practices with data engineering platforms.
• Understand how to manage large-scale DevOps data projects.
• Explore advanced DevOps patterns for data engineering (e.g., data observability, data mesh).
• Apply real world use cases for DevOps in data engineering.
• Leverage DevOps tools and frameworks for efficient data deployment.

Duration

10 Days

Course content

Module 1: Introduction to DevOps Data Engineering

• Fundamentals of data engineering and DevOps practices.
• Overview of CI/CD, IaC, and automated testing for data pipelines.
• Setting up a DevOps data engineering environment.
• Introduction to DevOps tools and methodologies.
• Best practices for DevOps data engineering.

Module 2: CI/CD for Data Pipelines

• Mastering continuous integration and continuous delivery (CI/CD) for data pipelines.
• Utilizing CI/CD tools for automated data pipeline deployments.
• Implementing automated build and deployment processes.
• Designing and building efficient CI/CD workflows.
• Best practices for data pipeline CI/CD.

Module 3: Infrastructure as Code (IaC)

• Utilizing infrastructure as code (IaC) for data infrastructure management.
• Implementing IaC with tools like Terraform and CloudFormation.
• Designing and building scalable data infrastructure.
• Optimizing IaC for data engineering deployments.
• Best practices for IaC.

Module 4: Automated Testing and Validation

• Implementing automated testing and validation for data engineering workflows.
• Utilizing testing frameworks for data quality checks.
• Designing and building automated test suites.
• Optimizing testing for continuous validation.
• Best practices for automated testing.

Module 5: Data Pipeline Deployment Strategies

• Designing and building efficient data pipeline deployment strategies.
• Utilizing containerization and orchestration (Docker, Kubernetes).
• Implementing blue/green and canary deployments.
• Optimizing deployments for minimal downtime.
• Best practices for deployment strategies.

Module 6: Workflow Automation and Scalability

• Optimizing data engineering workflows for automation and scalability.
• Utilizing workflow orchestration tools (Airflow, Prefect).
• Implementing automated data pipeline monitoring.
• Designing scalable data processing systems.
• Best practices for automation.

Module 7: Troubleshooting DevOps Data Implementations

• Troubleshooting and addressing common issues in DevOps data implementations.
• Analyzing CI/CD logs and deployment errors.
• Utilizing problem-solving techniques for resolution.
• Resolving common DevOps data errors.
• Best practices for troubleshooting.

Module 8: Data Governance and Security in DevOps

• Implementing data governance and security in DevOps data environments.
• Utilizing data access control and audit logs.
• Designing and building compliance frameworks.
• Optimizing security for DevOps data pipelines.
• Best practices for governance.

Module 9: Integration with DevOps Tools

• Integrating DevOps tools and practices with data engineering platforms.
• Utilizing version control systems (Git) for data pipelines.
• Implementing monitoring and logging tools (Prometheus, ELK).
• Designing efficient tool integrations.
• Best practices for tool integration.

Module 10: Large-Scale DevOps Data Projects

• Understanding how to manage large-scale DevOps data projects.
• Utilizing program and portfolio management techniques.
• Implementing scaled DevOps practices for data teams.
• Designing scalable DevOps solutions for data projects.
• Best practices for large scale DevOps.

Module 11: Advanced DevOps Patterns

• Exploring advanced DevOps patterns for data engineering (data observability, data mesh).
• Utilizing data observability tools for pipeline monitoring.
• Implementing DevOps for data mesh architectures.
• Designing and building advanced DevOps frameworks.
• Optimizing advanced patterns for specific applications.
• Best practices for advanced DevOps.

Module 12: Real-World Use Cases

• Implementing DevOps for data lake deployments.
• Utilizing DevOps for machine learning pipeline automation.
• Implementing DevOps for real-time data streaming.
• Utilizing DevOps for data warehouse migrations.
• Best practices for real-world applications.

Module 13: DevOps Tools Implementation

• Utilizing DevOps tools and frameworks (Jenkins, GitLab CI, ArgoCD).
• Implementing DevOps pipelines with specific tools.
• Designing and building automated workflows.
• Optimizing tool usage for efficient deployment.
• Best practices for tool implementation.

Module 14: Pipeline Monitoring and Metrics

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

Module 15: Future Trends in DevOps Data Engineering

• Emerging trends in DevOps for data engineering.
• Utilizing AI for DevOps automation in data pipelines.
• Implementing serverless DevOps for data processing.
• 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.