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Azure Data Engineer Online Training
One of the top providers of online IT training worldwide is VISWA Online Trainings. To assist beginners and working professionals in achieving their career objectives and taking advantage of our best services, We provide a wide range of courses and online training.
About Course
🌐 What Is Azure Data Engineer?
An Azure Data Engineer is a skilled professional responsible for designing, building, managing, and optimizing data pipelines and data storage solutions within the Microsoft Azure ecosystem. The Azure Data Engineer Training equips learners with the expertise to work on end-to-end data integration, transformation, and analytics workflows using Azure’s powerful data services.
This training focuses on real-world applications of Azure Data Factory, Azure Databricks, Azure Synapse Analytics, Azure Data Lake, and Azure SQL — enabling professionals to design secure, scalable, and high-performance data architectures for business insights and AI-driven solutions.
Core Capabilities Include:
- Data Ingestion & Integration: Design and manage pipelines using Azure Data Factory.
- Data Transformation: Process big data using Azure Databricks and PySpark.
- Data Storage & Management: Store structured and unstructured data in Azure Data Lake, Synapse, and SQL Database.
- Data Security & Compliance: Implement access control, encryption, and data governance.
- Real-Time Data Streaming: Use Event Hubs, Stream Analytics, and IoT Hub for live data processing.
- Analytics & Visualization: Enable reporting and insights with Power BI integration.
📊 Course Features Typically Included
Top online training platforms (like Viswa Online Trainings, Udemy, Coursera, and Microsoft Learn) offer the following features for Azure Data Engineer Training:
- ✅ Live instructor-led classes and recorded tutorials
- ✅ Hands-on labs and projects in Azure environments
- ✅ Real-time data pipeline and ETL project scenarios
- ✅ Certification and interview preparation support
- ✅ Lifetime access to Azure learning materials, labs, and recordings
- ✅ Step-by-step guidance for deploying and managing enterprise data solutions
🎓 Key Learning Outcomes
After completing the Azure Data Engineer Training, learners will be able to:
- Understand Azure Data Engineering architecture and services
- Build and orchestrate data pipelines using Azure Data Factory
- Process and transform data with Azure Databricks (PySpark)
- Design and manage data storage with Azure Synapse Analytics and Data Lake
- Implement security, monitoring, and governance for data solutions
- Perform real-time analytics using Azure Stream Analytics and Event Hubs
- Integrate Azure data solutions with Power BI for visualization and reporting
- Optimize data workflows and ensure performance efficiency across pipelines
Roles Prepared For:
- Azure Data Engineer
- Data Engineer (Cloud / Big Data)
- Data Analytics Engineer
- ETL Developer
- Azure Solution Architect
📍 Bonus: Certification Tracks
Learners can pursue globally recognized certifications such as:
- 🏅 Microsoft Certified: Azure Data Engineer Associate (DP-203)
- 🏅 Microsoft Certified: Azure Solutions Architect Expert
- 🏅 Databricks Certified Data Engineer
- 🏅 Viswa Online Trainings – Azure Data Engineer Professional Certification
Azure Data Engineer Training Course Syllabus
Azure Fundamentals and Data Fundamentals
- Core Azure Services
- Azure Services
- Service Models
- Benefits of Cloud
- Key Roles and Responsibilities
Azure Cost Management + Billing
- Azure Products and Services
- Azure free account creation
- Pricing calculator
- Cost optimization strategies
Azure SQL Server and Database
- Elastic Pool
- Compute + Storage
- Redundancy
- Configuring connectivity and firewall
- Defender
- Data source
- Pricing
SQL for Data Engineering
- Overview of Azure Data Studio
- Understanding Structured Query Language
- DML and DDL
- Create
- Insert
- Update
- Delete
- Truncate
- Drop
- TOP, Distinct
- Creating a backup table
- Joins and other clauses
- Filtering and grouping with having
- Stored Procedure
Azure Data Factory
- Pipeline
- Data Sets
- Activities
- Copy Data
- Stored Procedure
- Get Metadata
- ForEach
- Script
- Wait
- Data Flow
- A few more…
- Integration runtimes
- Azure
- Self-Hosted
- Azure-SSIS
- Linked Services
- Copy activity to migrate data from Azure Data Lake store.
- Monitoring and troubleshooting
- Scheduling the data pipeline
- Working with parameters and variables
- Data flow debug
- Overwriting a Dataset in dataflow
- Triggers
- Schedule
- Tumbling
- Storage Event
- Custom Events
- Initial load vs Incremental Load
- GitHub Configuration
- Data factory pricing
Azure Data Factory Advanced
- Working with incremental data
- Transformations
- Filter
- Select
- Sort
- Join
- Derived Column
- Conditional Split
- New Branch
- Alter Row
- Aggregate
- Union
- Sort
- A few more…
- Copying on premise data to azure
Azure Storage Account and Data Lake Store Gen 2
- Overview and Provisioning of Storage
- Provisioning Azure Data Lake Store Gen 2
- Uploading/Downloading blob
- The Account Key and SAS Token
- Storage Explorer
- Recovery
- Security
- Storage Account Pricing
Azure Databricks
- Hadoop
- The processing engine- Apache Spark and its features
- Spark Context, Spark Session
- The Azure Databricks as unified solution
- Azure Databricks Features, Components
- PySpark, Python
- Databricks Workspace
- Databricks Runtime
- Databricks Cluster
- Driver and worker
- Databricks Jobs
- Creating and managing Notebook
- Using Markdown and cells
- PySpark DataFrames
- Working with Spark SQL
- User Defined Functions
- Extract, Transform and Load
- Connecting to database
- Connecting to data lake gen2
- Transformations
- Filter
- Union
- Join
- Join Best Practises
- Derived Column
- Conditional Split
- Pivot
- Unpivot
- Sorting
- Few more…
- Workflows
- DBFS
- Delta Tables
- Catalog
- AI Assistant
Azure Logic apps
- Automation
Azure Resource Group
- Organization and Management
- Lifecycle Management
Azure Tags
- Key-value pairs
- Logical Grouping
- Cost Management and Allocation
Azure Key Vault
- Store and Manage Secrets
- Role Assignment
- Secret Creation
- Linked Service
Azure Data Engineer Course Key Features
- Live Instructor based training with software
- Certification Oriented content
- Hands-on complete Realtime training
- Flexible schedule demo's & classes
- Live recorded videos access
- Study material provided
- JOB Assistance
Course completion certificate
Azure Data Engineer Training - Upcoming Batches
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CHOOSE YOUR OWN COMFORTABLE LEARNING EXPERIENCE
Live Virtual Training
- Schedule your sessions at your comfortable with timings
- Instructor-Led training real time projects
- Certification Guidance
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Self-Paced Learning
- Complete set of live-online training session recorded videos.
- Learn technology at your own pace.
- Get access for lifetime.
Corporate Training
- Learn as a full day schedule with discussions, exercises.
- Practical use cases.
- Design your own syllabus based
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Azure Data Engineer Online Training FAQ'S
What does an Azure Data Engineer do in an organization?
An Azure Data Engineer designs and builds secure, scalable data pipelines that support analytics, reporting, and AI initiatives using Azure cloud services.
What is Azure Data Factory and why is it important?
Azure Data Factory is a serverless data integration tool that enables building ETL and ELT workflows to move and transform data at scale.
How does Azure Synapse Analytics support business intelligence?
Azure Synapse offers data warehousing and analytics capabilities, combining big data and relational data for enterprise-grade reporting.
What role does Azure Databricks play in Azure data solutions?
Azure Databricks supports data engineering, data science, and machine learning workflows, making it key for advanced analytics solutions
How is security managed in Azure Data Engineering projects?
Security is enforced through Azure AD authentication, RBAC, data encryption, and Key Vault integration to protect sensitive data.
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