Azure Data Engineering Services (data Factory, Synapse Analytics) Training Course: Azure Data Solutions

Introduction

Empower your data infrastructure with our Azure Data Engineering Services (Data Factory, Synapse Analytics) Training Course. This program is designed to equip you with the essential skills to build data solutions on the Microsoft Azure platform, enabling you to design and deploy scalable and efficient data architectures. In today's data-driven world, mastering Azure data engineering tools is crucial for organizations seeking to derive actionable insights from their data. Our Azure data engineering training course offers hands-on experience and expert guidance, empowering you to leverage Azure Data Factory and Synapse Analytics for diverse data engineering tasks.

This Azure data solutions training delves into the core concepts of Azure data engineering, covering topics such as data integration, data warehousing, and analytics. You'll gain expertise in using industry-standard Azure services to build data solutions on the Microsoft Azure platform, meeting the demands of modern data-intensive organizations. Whether you're a data engineer, data architect, or cloud developer, this Azure Data Engineering Services (Data Factory, Synapse Analytics) course will empower you to design and implement high-performance data solutions on the Azure platform.

Target Audience:

• Data Engineers
• Data Architects
• Cloud Developers
• Data Analysts
• Database Administrators
• Business Intelligence Developers
• Anyone needing Azure data engineering skills

Course Objectives:

• Understand the fundamentals of Azure data engineering services (Data Factory, Synapse Analytics).
• Master Azure Data Factory for data integration and ETL processes.
• Utilize Azure Synapse Analytics for data warehousing and analytics.
• Implement data pipelines and data flows in Azure.
• Design and build scalable data solutions on the Azure platform.
• Optimize Azure data services for performance and cost-effectiveness.
• Troubleshoot and address common challenges in Azure data engineering.
• Implement data security and access control in Azure data services.
• Integrate Azure data services with other Azure and third-party tools.
• Understand how to handle large datasets and data warehousing in Azure.
• Explore advanced Azure data engineering features (e.g., Synapse Pipelines, Spark integration).
• Apply real world use cases for Azure data engineering services.
• Leverage Azure's ecosystem for efficient data engineering workflows.

Duration

10 Days

Course content

Module 1: Introduction to Azure Data Engineering Services

• Fundamentals of Azure data engineering services (Data Factory, Synapse Analytics).
• Overview of data integration, data warehousing, and analytics on Azure.
• Setting up an Azure data engineering development environment.
• Introduction to Azure Data Factory and Synapse Analytics.
• Best practices for Azure data engineering.

Module 2: Azure Data Factory for Data Integration

• Mastering Azure Data Factory for data integration and ETL processes.
• Utilizing pipelines, datasets, and linked services.
• Designing and building data integration workflows.
• Optimizing Data Factory pipelines for performance.
• Best practices for Azure Data Factory.

Module 3: Azure Synapse Analytics for Data Warehousing

• Utilizing Azure Synapse Analytics for data warehousing and analytics.
• Implementing SQL pools and Spark pools.
• Designing and building data warehouses with Synapse.
• Optimizing Synapse queries for analytical workloads.
• Best practices for Azure Synapse Analytics.

Module 4: Data Pipelines and Data Flows

• Implementing data pipelines and data flows in Azure.
• Utilizing mapping data flows for visual data transformation.
• Designing and building complex data pipelines.
• Optimizing data flows for performance and scalability.
• Best practices for data pipelines.

Module 5: Scalable Data Solutions on Azure

• Designing and building scalable data solutions on the Azure platform.
• Utilizing Azure storage and compute resources.
• Implementing data ingestion, transformation, and loading (ETL).
• Optimizing solutions for large-scale data processing.
• Best practices for Azure data solutions.

Module 6: Performance and Cost Optimization

• Optimizing Azure data services for performance and cost-effectiveness.
• Utilizing performance tuning and monitoring tools.
• Implementing data partitioning and compression strategies.
• Designing cost-effective data solutions.
• Best practices for optimization.

Module 7: Troubleshooting Azure Data Engineering

• Debugging common challenges in Azure data engineering.
• Analyzing Azure service logs and error messages.
• Utilizing troubleshooting techniques for problem resolution.
• Resolving common data engineering issues.
• Best practices for troubleshooting.

Module 8: Data Security and Access Control

• Implementing data security and access control in Azure data services.
• Utilizing Azure Active Directory and RBAC.
• Designing and building secure data solutions.
• Optimizing security for data protection.
• Best practices for security.

Module 9: Integration with Azure and Third-Party Tools

• Integrating Azure data services with other Azure and third-party tools.
• Utilizing Azure Blob Storage, Azure Databricks, and Power BI.
• Implementing data integration with external data sources.
• Optimizing integration for data retrieval and analysis.
• Best practices for integration.

Module 10: Large Datasets and Data Warehousing

• Understanding how to handle large datasets and data warehousing in Azure.
• Utilizing Synapse dedicated SQL pools and serverless SQL pools.
• Implementing data partitioning and parallel processing.
• Designing scalable data warehousing solutions.
• Best practices for large datasets.

Module 11: Advanced Azure Data Engineering Features

• Exploring advanced Azure data engineering features (Synapse Pipelines, Spark integration).
• Utilizing Synapse Pipelines for orchestration.
• Implementing Spark integration for data processing.
• Designing and building advanced data engineering solutions.
• Optimizing advanced techniques for specific applications.
• Best practices for advanced features.

Module 12: Real-World Use Cases

• Implementing Azure data engineering for real-time analytics and monitoring.
• Utilizing Azure data services for data warehousing and business intelligence.
• Implementing Azure data engineering for machine learning and data science.
• Utilizing Azure data engineering for log processing and data analysis.
• Best practices for real-world applications.

Module 13: Azure Data Engineering Tools Implementation

• Utilizing Azure data engineering tools and frameworks (Azure DevOps, Azure CLI).
• Implementing data pipelines with specific tools.
• Designing and building automated data workflows.
• Optimizing tool usage for efficient development.
• Best practices for tool implementation.

Module 14: Performance Monitoring and Logging

• Implementing performance monitoring and logging for Azure data services.
• Utilizing Azure Monitor and Log Analytics.
• Designing and building performance dashboards.
• Optimizing monitoring for real-time insights.
• Best practices for monitoring.

Module 15: Future Trends in Azure Data Engineering

• Emerging trends in Azure data engineering.
• Utilizing AI for data pipeline automation.
• Implementing data mesh architectures on Azure.
• 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.