Azure Data Engineering

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Breadcrumb Abstract Shape
Breadcrumb Abstract Shape
Breadcrumb Abstract Shape
Breadcrumb Abstract Shape

This course provides in-depth training on designing and implementing data solutions using Microsoft Azure’s data platform. It is designed for individuals looking to build expertise in data ingestion, transformation, storage, and analysis using Azure services such as Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, and Azure Databricks.

Through real-world projects and guided labs, learners will develop the skills necessary to work with both structured and unstructured data at scale, build end-to-end ETL pipelines, and ensure data quality, governance, and security in the cloud.

What Will You Learn?
  • By the end of this course, learners will be able to:
  • Understand the core components of Azure’s data ecosystem
  • Design and build scalable data pipelines using Azure Data Factory
  • Perform big data processing and analytics using Azure Synapse Analytics and Azure Databricks
  • Store, manage, and secure data in Azure Data Lake Storage Gen2 and Azure SQL Database
  • Implement data partitioning, indexing, and performance tuning strategies
  • Monitor data pipelines, troubleshoot issues, and apply best practices for data governance and security
  • By the end of this course, learners will be able to:
  • Understand the core components of Azure’s data ecosystem
  • Design and build scalable data pipelines using Azure Data Factory
  • Perform big data processing and analytics using Azure Synapse Analytics and Azure Databricks
  • Store, manage, and secure data in Azure Data Lake Storage Gen2 and Azure SQL Database
  • Implement data partitioning, indexing, and performance tuning strategies
  • Monitor data pipelines, troubleshoot issues, and apply best practices for data governance and security.

Audience

  • This course is ideal for:
  • Aspiring and current data engineers who want to specialize in Azure-based data solutions
  • ETL developers and data warehouse specialists transitioning to cloud-native data engineering
  • Data analysts and BI developers seeking to automate and scale their data workflows in the cloud
  • Software developers and IT professionals looking to build expertise in data pipelines and big data tools

Course Content

Beginner Level
🎯 Goal: Understand core Azure services and basic data workflows. 1. Introduction to Azure & Data Engineering • What is Azure? Key services overview • Role of a Data Engineer • Azure global infrastructure, regions, and SLAs • Azure Portal, Azure CLI, Resource Groups, and ARM templates 2. Core Azure Data Services • Azure Storage (Blob, ADLS Gen2, Table, Queue) • Azure SQL Database & Azure Managed Instance • Azure Synapse Analytics (formerly SQL DW) – intro • Azure Cosmos DB – overview 3. Basics of Data Ingestion • What is ETL vs ELT? • Data ingestion using Azure Data Factory (ADF) • Pipelines, Linked Services, Datasets • Integration Runtimes & Triggers

Intermediate Level
🎯 Goal: Build scalable ETL pipelines, transform data, and handle security. 4. Azure Data Factory (ADF) Deep Dive • Activities: Copy, Data Flow, Web, Lookup • Mapping Data Flows vs Wrangling Data Flows • Parameterization & Expressions • Monitoring & Alerts • CI/CD for ADF using Azure DevOps 5. Azure Synapse Analytics • Dedicated vs Serverless SQL Pools • Ingesting data using COPY INTO, PolyBase • On-demand SQL querying with Serverless Pool • Building Data Lakehouse architecture • Integrating Synapse with ADF & Power BI 6. Data Storage & Transformation • Delta Lake on Azure • Working with Azure Data Lake Gen2 • Data transformation with Azure Databricks • Data cleansing and standardization • Notebooks, jobs, and clusters in Databricks 7. Security & Governance • Role-Based Access Control (RBAC) • Managed Identities • Data Masking, Encryption at Rest & Transit • Azure Key Vault integration • Azure Purview for Data Cataloging

Advanced Level
🎯 Goal: Optimize, monitor, and deploy enterprise-grade pipelines. 8. Advanced Data Engineering Concepts • Partitioning strategies • Data orchestration & dependency management • Handling late-arriving data • Incremental loads & watermarking • Slowly Changing Dimensions (SCD) 9. Monitoring, Logging & Performance Tuning • Monitoring ADF & Synapse pipelines • Using Azure Monitor, Log Analytics • Diagnosing failures and performance bottlenecks • Optimization of data flows and queries 10. Real-time and Streaming Data • Azure Event Hubs • Azure Stream Analytics • Capturing and processing streaming data • Stream-to-Lake and Stream-to-Warehouse patterns 11. Data Integration & Reporting • Power BI with Synapse / Azure SQL • Building semantic models • Row-Level Security in Power BI • Exporting data to external sources (Snowflake, AWS, etc.)

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Course Includes:

  • Price:Free
  • Instructor:admin
  • Duration: 60 minutes
  • Lessons:0
  • Students:0
  • Level:All Levels
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