Get DP203 Certification: Azure Data Engineer Associate
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Description of the training
This training allows you to acquire the skills needed to design, implement and manage data management solutions on Azure, using tools such as Azure Data Factory, Azure Synapse Analytics and Azure Databricks. You will learn how to manage complex data flows and ensure data security and compliance in a cloud environment.
Objectives of training
At the end of this training, participants will be able to:
- Understand the concepts of Azure data engineering.
- Implement solutions for ingestion, transformation and storage of data.
- Design and optimize data pipelines for analytical workloads.
- Ensure the security and compliance of stored and in-transit data.
- Monitor and optimize data solutions in production.
Who is this training for?
The training is aimed at a wide audience, including:
- Data Engineers: Responsible for designing and managing data pipelines.
- Cloud Architects: Creating analytical solutions on Azure.
- BI Developers: Wishing to take advantage of Azure's advanced data tools.
- Database Administrators: Migrating or managing cloud data systems.
- Data Professionals: Working with large-scale data streams.
Prerequisites
No specific prerequisites are required. This training is available to anyone interested in learning about Azure Cloud data engineering. However, a basic knowledge of IT or information systems can be an asset.
Training programme
Day 1: Introduction to Azure Data Engineering
- Presentation of Azure services for data management.
- Data Ingestion Concepts: Batch and Real Time.
- Demonstration: Creation of a simple pipeline with Azure Data Factory.
- Development of ETL/ELT solutions with Azure Data Factory.
- Integration with Azure SQL Database and Synapse Analytics.
- Practical workshop: ETL Pipeline from end to end.
- Implementation of security strategies: encryption, access control.
- Introduction to Azure Purview for data governance.
- Demonstration: Configure governance on a dataset.
- Pipeline monitoring with Azure Monitor and Log Analytics.
- Optimizing the performance of analytical solutions.
- Summary: Preparation for the DP-203 review and feedback on practical workshops.
Training assets
- Pedagogical approach: An alternative between theory and practice for better assimilation of concepts.
- Qualified speakers: Specialist trainers with practical experience in the field of data in Azure.
- Educational tools and materials: Access to online resources, live demonstrations and real-life case studies.
- Accessibility: Training is open to all, without advanced technical prerequisites.
Pedagogical methods and tools used
- Live Demonstrations: Interaction with data engineering services on the Azure cloud.
- Practical workshops and real case studies: Application of concepts in various sectors.
- Feedback: Sharing best practices and common mistakes in business.
- Simulations and tools: Using Azure data engineering resources in interactive workshops.
Evaluation
- MCQ at the end of training.
- Practical case studies.
- Continuous evaluation with personalized feedback.
Normative References
- Azure Well-Architected Framework
- ISO/IEC 19086
- GDPR (General Data Protection Regulation)
- NIST Cloud Computing Standards (SP 500-292)
- ISO 27001 Information security