Azure Data Engineering
Overview
Dive into the world of cloud-based data solutions with our comprehensive Azure Data Engineering course. Designed to equip learners with the skills to build, manage, and optimize modern data platforms on Microsoft Azure, this course provides a robust foundation in data engineering, empowering professionals to handle real-world data challenges effectively.
What You’ll Learn
- Data Storage & Management
- Learn to design and implement scalable, durable data storage solutions using Azure services such as Azure Data Lake, Blob Storage, and Azure SQL Server.
- Understand how to store data efficiently and securely, ensuring quick access and effective retrieval strategies.
- Data Integration
- Master the art of data movement using Azure Data Factory for orchestrating data workflows across multiple environments.
- Learn about ETL/ELT processes, data pipelines, and how to integrate data from disparate sources.
- Big Data Processing
- Gain hands-on experience with Azure Databricks, Apache Spark, and Azure Synapse Analytics to process large datasets and implement big data solutions.
- Understand distributed computing principles to handle massive volumes of data with ease.
- Security & Monitoring
- Ensure data security with Azure Key Vault, encryption techniques, and Azure Active Directory integrations.
- Learn how to monitor and optimize data pipelines using Azure Monitor and Azure Log Analytics to ensure smooth operations and resolve issues promptly.
- Data Governance
- Implement data governance and compliance using Azure Purview, ensuring data quality, consistency, and regulatory adherence across the organization.
- Azure Data Factory & Azure Databricks Integration
- This module teaches you how to seamlessly integrate Azure Data Factory (ADF) with Azure Databricks to build efficient, scalable ETL pipelines.
- You will learn to orchestrate data workflows in ADF, triggering Databricks for powerful data processing and transformations using Apache Spark.
- Key topics include automating data movement, performing complex transformations, and scheduling pipeline execution. You’ll also master monitoring and error handling, ensuring robust and reliable workflows.
- Real-world examples will demonstrate how to apply these skills in industries such as retail, finance, and healthcare, enabling advanced analytics capabilities.
Hands-on Labs
Gain practical experience through hands-on labs where you’ll design, build, and optimize end-to-end data engineering pipelines on Azure. You’ll work on real-world projects that involve data ingestion, processing, storage, and analytics, preparing you for complex data engineering tasks.
Realtime Project
This project focuses on building an end-to-end data engineering solution using Microsoft Azure. You’ll design and implement a scalable data pipeline, integrating services like Azure Data Factory, Azure Databricks, and Azure Data Lake for data ingestion, transformation, and storage. The project will involve working with large datasets, automating ETL workflows, and applying big data processing using Apache Spark.
Who Should Enroll?
- Data Engineers looking to enhance their cloud expertise and move towards Azure-based data solutions.
- Data Analysts or Developers aiming to transition into data engineering roles.
- IT Professionals interested in mastering Azure’s data services to architect scalable and efficient data solutions.
Prerequisites
Basic knowledge of database systems, SQL, and some experience with programming languages like Python or Scala is recommended but not mandatory. Familiarity with cloud concepts will be a plus.
Course Format
- Duration: 8-10 weeks
- Mode: Online
- Includes: Live Sessions, Video Tutorials, Quizzes, Projects, and Labs