Data Pipelines & Etl Development Training Course: Efficient Data Integration

Introduction

Streamline your data workflows with our Data Pipelines and ETL Development Training Course. This program is designed to equip you with the essential skills to build efficient data pipelines for data integration, enabling you to create robust and scalable data management solutions. In today's data-driven world, mastering data pipelines and ETL is crucial for ensuring the reliability, consistency, and accessibility of data across various systems. Our data pipelines training course offers hands-on experience and expert guidance, empowering you to implement state-of-the-art data integration practices.

This ETL development training delves into the core concepts of data pipelines, covering topics such as data extraction, transformation, and loading, as well as pipeline orchestration and monitoring. You'll gain expertise in using industry-standard tools and platforms to build efficient data pipelines for data integration, meeting the demands of modern data engineering projects. Whether you're a data engineer, data architect, or data analyst, this Data Pipelines & ETL Development course will empower you to build and maintain high-performance data integration systems.

Target Audience:

• Data Engineers
• Data Architects
• Data Analysts
• ETL Developers
• Database Administrators
• Software Developers
• Anyone needing data pipelines and ETL skills

Course Objectives:

• Understand the fundamentals of data pipelines and ETL development.
• Master data extraction from various data sources.
• Utilize data transformation techniques for data cleaning and preparation.
• Implement data loading into data warehouses and data lakes.
• Design and build efficient data pipelines for data integration.
• Optimize data pipelines for performance and scalability.
• Troubleshoot and address common data pipeline challenges.
• Implement data pipeline monitoring and logging.
• Integrate data pipelines with real-world data systems.
• Understand how to handle data quality and data governance.
• Explore advanced data pipeline techniques (e.g., streaming data pipelines, serverless ETL).
• Apply real world use cases for data pipelines and ETL.
• Leverage data pipeline tools and platforms for efficient development.

Duration

10 Days

Course content

Module 1: Introduction to Data Pipelines and ETL Development

• Fundamentals of data pipelines and ETL development.
• Overview of data extraction, transformation, and loading (ETL).
• Setting up a data pipeline development environment.
• Introduction to data pipeline tools and platforms.
• Best practices for data pipelines.

Module 2: Data Extraction

• Implementing data extraction from relational databases.
• Utilizing APIs and web scraping for data extraction.
• Designing and building data extraction pipelines.
• Optimizing extraction for various data sources.
• Best practices for data extraction.

Module 3: Data Transformation

• Implementing data transformation techniques (data cleaning, aggregation).
• Utilizing data quality checks and validation.
• Designing and building data transformation pipelines.
• Optimizing transformations for data preparation.
• Best practices for data transformation.

Module 4: Data Loading

• Implementing data loading into data warehouses and data lakes.
• Utilizing batch and incremental loading techniques.
• Designing and building data loading pipelines.
• Optimizing loading for data storage and retrieval.
• Best practices for data loading.

Module 5: Data Pipeline Design

• Designing efficient data pipelines for data integration.
• Implementing pipeline orchestration and scheduling.
• Utilizing workflow management tools (Airflow, Prefect).
• Optimizing pipeline design for performance.
• Best practices for pipeline design.

Module 6: Pipeline Optimization and Scalability

• Optimizing data pipelines for performance and scalability.
• Utilizing parallel processing and distributed computing.
• Implementing data partitioning and sharding.
• Designing scalable data integration solutions.
• Best practices for pipeline optimization.

Module 7: Troubleshooting Data Pipeline Challenges

• Debugging common data pipeline issues.
• Analyzing pipeline performance and errors.
• Utilizing troubleshooting techniques for problem resolution.
• Resolving common data pipeline challenges.
• Best practices for troubleshooting.

Module 8: Data Pipeline Monitoring and Logging

• Implementing data pipeline monitoring and logging.
• Utilizing logging and alerting for pipeline health.
• Designing and building monitoring dashboards.
• Optimizing monitoring for real-time insights.
• Best practices for monitoring.

Module 9: Integration with Real-World Data Systems

• Integrating data pipelines with real-world data systems.
• Utilizing APIs and data connectors.
• Implementing data pipelines for various applications.
• Optimizing integration for business impact.
• Best practices for integration.

Module 10: Data Quality and Data Governance

• Implementing data quality checks and validation.
• Utilizing data governance frameworks.
• Designing and building data quality pipelines.
• Optimizing data handling for compliance.
• Best practices for data quality.

Module 11: Advanced Data Pipeline Techniques

• Implementing streaming data pipelines (Kafka, Flink).
• Utilizing serverless ETL and data pipelines.
• Designing and building advanced data integration solutions.
• Optimizing advanced techniques for specific applications.
• Best practices for advanced techniques.

Module 12: Real-World Use Cases

• Implementing data pipelines for e-commerce data integration.
• Utilizing data pipelines for financial data warehousing.
• Implementing data pipelines for healthcare data analysis.
• Utilizing data pipelines for marketing data aggregation.
• Best practices for real-world applications.

Module 13: Data Pipeline Tools and Platforms Implementation

• Utilizing Apache Airflow for pipeline orchestration.
• Implementing data pipelines with AWS Glue and Google Cloud Dataflow.
• Designing and building data pipelines with tools.
• Optimizing tool usage for efficient development.
• Best practices for tool implementation.

Module 14: Data Pipeline Security and Performance

• Implementing data pipeline security measures.
• Utilizing data encryption and access control.
• Designing and building secure data pipelines.
• Optimizing pipelines for performance and security.
• Best practices for security and performance.

Module 15: Future Trends in Data Pipelines

• Emerging trends in data pipeline development.
• Utilizing AI for data pipeline automation.
• Implementing data mesh and data fabric architectures.
• Best practices for future data pipelines.

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.