Data Engineering Testing & Validation Training Course: Quality Data Assurance

Introduction

Fortify your data infrastructure with our Data Engineering Testing and Validation Training Course. This program is designed to equip you with the essential skills to ensure data quality through testing, enabling you to build reliable and trustworthy data systems. In today's data-driven world, mastering data testing and validation is crucial for organizations seeking to maintain data integrity and accuracy. Our data testing training course offers hands-on experience and expert guidance, empowering you to implement robust testing strategies for diverse data engineering workflows.

This quality data assurance training delves into the core concepts of data engineering testing, covering topics such as data quality checks, pipeline validation, and automated testing frameworks. You'll gain expertise in using industry-standard tools and techniques to ensure data quality through testing, meeting the demands of modern data-intensive environments. Whether you're a data engineer, data quality analyst, or data architect, this Data Engineering Testing and Validation course will empower you to build and maintain high-quality data solutions.

Target Audience:

• Data Engineers
• Data Quality Analysts
• Data Architects
• Data Scientists
• DevOps Engineers
• QA Engineers
• Anyone needing data testing and validation skills

Course Objectives:

• Understand the fundamentals of data engineering testing and validation.
• Master data quality checks and validation techniques.
• Utilize automated testing frameworks for data pipelines.
• Implement data profiling and schema validation.
• Design and build data testing strategies for various data workflows.
• Optimize data testing for performance and reliability.
• Troubleshoot and address common issues in data testing implementations.
• Implement data governance and compliance testing.
• Integrate data testing with CI/CD pipelines.
• Understand how to handle large-scale data testing.
• Explore advanced data testing patterns (e.g., contract testing, data anomaly detection).
• Apply real world use cases for data engineering testing.
• Leverage data testing tools and frameworks for efficient validation.

Duration

10 Days

Course content

Module 1: Introduction to Data Engineering Testing

• Fundamentals of data engineering testing and validation.
• Overview of data quality checks, pipeline validation, and automated testing.
• Setting up a data testing development environment.
• Introduction to data testing tools and frameworks.
• Best practices for data testing.

Module 2: Data Quality Checks and Validation

• Mastering data quality checks and validation techniques.
• Utilizing data profiling and schema validation.
• Implementing data consistency and integrity checks.
• Designing and building data quality validation pipelines.
• Best practices for data quality.

Module 3: Automated Testing Frameworks

• Utilizing automated testing frameworks for data pipelines.
• Implementing unit testing and integration testing.
• Designing and building automated test suites.
• Optimizing testing for continuous integration.
• Best practices for automated testing.

Module 4: Data Profiling and Schema Validation

• Implementing data profiling and schema validation.
• Utilizing data profiling tools and techniques.
• Designing and building schema validation pipelines.
• Optimizing validation for data integrity.
• Best practices for schema validation.

Module 5: Data Testing Strategies

• Designing and building data testing strategies for various data workflows.
• Utilizing test-driven development (TDD) for data pipelines.
• Implementing testing strategies for ETL and data warehousing.
• Designing efficient data testing plans.
• Best practices for testing strategies.

Module 6: Performance and Reliability Testing

• Optimizing data testing for performance and reliability.
• Utilizing load testing and stress testing.
• Implementing performance monitoring and analysis.
• Designing reliable testing environments.
• Best practices for performance testing.

Module 7: Troubleshooting Testing Implementations

• Troubleshooting and addressing common issues in data testing implementations.
• Analyzing test logs and error messages.
• Utilizing problem-solving techniques for resolution.
• Resolving common testing errors.
• Best practices for troubleshooting.

Module 8: Data Governance and Compliance Testing

• Implementing data governance and compliance testing.
• Utilizing data security and access control testing.
• Designing and building compliance testing frameworks.
• Optimizing testing for regulatory requirements.
• Best practices for governance.

Module 9: Integration with CI/CD Pipelines

• Integrating data testing with CI/CD pipelines.
• Utilizing CI/CD tools for automated testing.
• Implementing continuous data validation.
• Designing efficient testing integrations.
• Best practices for CI/CD integration.

Module 10: Large-Scale Data Testing

• Understanding how to handle large-scale data testing.
• Utilizing distributed testing frameworks.
• Implementing data sampling and aggregation for testing.
• Designing scalable testing solutions.
• Best practices for large scale testing.

Module 11: Advanced Data Testing Patterns

• Exploring advanced data testing patterns (contract testing, data anomaly detection).
• Utilizing contract testing for data integration.
• Implementing data anomaly detection for quality assurance.
• Designing and building advanced testing solutions.
• Optimizing advanced patterns for specific applications.
• Best practices for advanced patterns.

Module 12: Real-World Use Cases

• Implementing data testing for e-commerce data pipelines.
• Utilizing data validation for financial transaction systems.
• Implementing data quality checks for healthcare data.
• Utilizing data testing for IoT data streams.
• Best practices for real-world applications.

Module 13: Data Testing Tools Implementation

• Utilizing data testing tools and frameworks (Great Expectations, dbt).
• Implementing data validation with specific tools.
• Designing and building automated testing scripts.
• Optimizing tool usage for efficient validation.
• Best practices for tool implementation.

Module 14: Test Monitoring and Metrics

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

Module 15: Future Trends in Data Testing

• Emerging trends in data engineering testing.
• Utilizing AI for automated test generation.
• Implementing data testing in cloud-native environments.
• 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.