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Introduction
Azure Data Engineering is a field that involves designing, implementing, and maintaining data management systems on the Azure cloud platform. Azure data engineers are responsible for a variety of tasks, including:
• Data integration: Consolidate data from different sources into a format that can be used to build analytics solutions
• Data storage: Create data warehouses to store analytical data
• Data processing: Build and maintain secure and compliant data processing pipelines
• Data modeling: Create models of data
• Data visualization: Help stakeholders understand the data through exploration
1.Quick Delivery
This course offers a clear introduction to Microsoft Azure, a top cloud computing platform. You’ll learn about Azure services, architecture, and essential tools like Virtual Machines, Storage, and SQL Database. Ideal for IT pros, developers, and cloud beginners, it covers using Azure Resource Manager (ARM) to manage resources, apply security features, and optimize performance and costs.
Certification Roadmap for Azure Data Engineers
Each certification in the Azure Data Engineer path builds upon the previous one, helping you progressively gain expertise.
• Azure Fundamentals (AZ-900) – for foundational knowledge.
• Azure Data Fundamentals (DP-900) – for core data concepts.
• Azure Data Engineer Associate (DP-203) – to specialize in data engineering.
• Azure AI Fundamentals (AI-900) – to understand AI integration.
• Azure Developer Associate (AZ-204) –for application development insights.
• Azure Solutions Architect Expert (AZ305) – for advanced architecture.
Certification 2 - Microsoft Certified: Azure Data Fundamentals
• Data concepts like relational and non-relational data.
• Basics of data warehousing, big data, and data analytics in Azure.
• Exposure to Azure SQL Database, Cosmos DB, and other core data services
Certification 3 - Microsoft Certified: Azure Data Engineer Associate
Focuses on designing and implementing data storage, processing, and security.
• Building and managing data pipelines and storage solutions.
• Working with big data analytics, data transformation, and data integration.
• Advanced skills in Azure Synapse Analytics, Databricks, and Azure Data Factory.
Certification 4 - Microsoft Certified:
Azure AI Fundamentals
Covers the basics of AI and machine learning in Azure.
• Basic principles of AI workloads and machine learning.
• Working with Azure AI services like Azure Machine Learning and Cognitive Services.
• Understanding AI ethics, security, and responsible AI.
Certification 5 - Microsoft Certified: Azure Developer Associate
Provides insights into developing, testing, and maintaining applications in Azure.
• Developing applications with Azure SDKs and APIs.
• Implementing cloud functions, app services, and serverless architectures.
• Collaborating on cross-functional data projects requiring coding and API management.
Certification 6 - Microsoft Certified: Azure Solutions Architect Expert
Prepares you for advanced solution design and architecture.
• Designing data solutions that ensure security, scalability, and resilience.
• Advanced understanding of cloud infrastructure, data storage, and business continuity.
• Working with a range of Azure services for integrated data solutions.
Certification 3 - Microsoft Certified: Azure Data Engineer Associate
Focuses on designing and implementing data storage, processing, and security.
• Building and managing data pipelines and storage solutions.
• Working with big data analytics, data transformation, and data integration.
• Advanced skills in Azure Synapse Analytics, Databricks, and Azure Data Factory.
Conclusion
Start with foundational knowledge and gradually build toward expert-level certifications. Identify the next step in your certification journey and start preparing with Pragra’s tailored azure data engineer training
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