Azure Data Engineer training
Azure data engineer course
Learning Path & Key Skills
The Azure Data Engineer course is mainly designed for people who want to build careers in data engineering, cloud data management, and analytics using Microsoft Azure. It focuses on tools and services in Azure that help organizations collect, store, transform, and analyze data.
1. Data Integration & ETL (Extract, Transform, Load)
Learn to use Azure Data Factory (ADF) to move and transform data from different sources.
Build pipelines that handle both batch and real-time data processing.
🔹 2. Data Storage & Management
Learn to store large-scale structured, semi-structured, and unstructured data in:
Azure Data Lake Storage (ADLS)
Azure SQL Database / Synapse Analytics
Cosmos DB
Understand data partitioning, indexing, and optimization for performance.
🔹 3. Big Data Processing
Work with Azure Synapse Analytics for data warehousing.
Use Azure Databricks (Apache Spark) for big data analytics and machine learning workflows.
Azure Synapse Analytics: An integrated analytics service that brings together data warehousing, big data processing, and data integration.
Azure Data Factory (ADF): A cloud-based ETL service for data integration and orchestration of data movement.
ÂAzure Databricks: An Apache Spark-based analytics platform optimized for the Azure cloud.
ÂAzure Data Lake Storage Gen2 (ADLS Gen2): A scalable and secure data lake solution built on Azure Blob Storage.
Azure Stream Analytics: A real-time analytics service for processing fast-moving streams of data.
Azure Devops Course Outline
Introduction to Azure DevOps
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- Overview of DevOps and its importance in modern software development
- Introduction to Azure DevOps tools and services
- Understanding Agile methodologies and Azure Boards
Version Control with Git and Azure Repos
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- Introduction to Git and version control concepts
- Managing repositories with Azure Repos
- Branching, merging, and pull requests
Continuous Integration (CI)
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- Setting up build pipelines in Azure Pipelines
- Automated testing and code quality checks
- Integration with GitHub and other repositories
Continuous Deployment (CD)
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- Configuring release pipelines for automated deployments
- Managing environments and approvals
- Deploying to Azure services (Web Apps, Kubernetes, VMs, etc.)
Hands-On Projects
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- Building and deploying a sample application using Azure DevOps
- Real-world scenarios to create CI/CD pipelines and manage infrastructure
Certification and Career Guidance
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- Preparation for the Microsoft Azure DevOps Engineer Expert certification
- Resume building and interview preparation
- Placement support and freelancing tips
Real-Time Data & Streaming
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Process streaming data using Azure Event Hubs, Stream Analytics, and integrate with Power BI for dashboards.
