The Getting Started with Azure Data Solutions course is designed for beginners, aspiring data engineers, data analysts, cloud professionals, and IT practitioners who want to build a strong foundation in Microsoft Azure’s data ecosystem.
This course introduces learners to core Azure data services used for data ingestion, processing, storage, analytics, and monitoring. You will explore how modern data solutions are designed end to end using services such as Azure Data Factory, Azure Synapse Analytics, Azure Data Lake Storage, Azure SQL, Azure Cosmos DB, Apache Spark, Microsoft Fabric, and Azure Monitor. Through a combination of conceptual explanations, demos, and real-world examples, this course helps you understand how data flows from ingestion to analytics in the Azure cloud. The course delivers approximately 8–10 hours of structured video content, organized into four modules. Each module includes quizzes and knowledge checks to reinforce learning and validate understanding. Enroll in Getting Started with Azure Data Solutions to gain practical knowledge of Azure data services and confidently begin your journey into cloud-based data engineering and analytics. Course Modules Module 1: Azure Data Engineering Fundamentals Understand the basics of Azure data engineering, including batch and stream processing concepts and the core services used to build data pipelines. Module 2: Azure Data Storage and Database Services Overview Explore Azure storage, database, and data lake services, and learn how to choose the right storage and database solution for different data scenarios. Module 3: Microsoft Azure End-to-End Data Analytics Learn how Azure Synapse Analytics, Apache Spark, and Microsoft Fabric enable large-scale analytics and modern data platform architectures. Module 4: Azure Data Monitoring, Ingestion, and Analytics Discover how to ingest, monitor, and analyze data using Azure Monitor, Azure Data Factory, Azure Databricks, and Azure Event Hubs. By the End of This Course, You Will Be Able To: Understand core Azure data engineering concepts and architectures Identify and use Azure services for data ingestion, processing, and analytics Design basic end-to-end data solutions in Microsoft Azure Work with Azure storage, databases, and data lakes effectively Analyze data using Azure Synapse Analytics, Apache Spark, and Microsoft Fabric Monitor and troubleshoot data pipelines using Azure monitoring tools Week 1 Overview – Azure Data Engineering Fundamentals In Week 1, you’ll be introduced to the fundamentals of Azure data engineering. You’ll learn what data engineering is, common data processing patterns, and the Azure services used for batch and stream processing. The week covers Azure Data Factory, Event Hubs, Stream Analytics, and Synapse Analytics, helping you understand how data is ingested and processed in the Azure cloud. By the end of this week, you’ll have a clear understanding of Azure’s data engineering landscape and how different services work together. Week 2 Overview – Azure Data Storage and Database Services Week 2 focuses on Azure’s storage and database offerings. You’ll explore Azure SQL, Azure SQL Managed Instance, SQL Server on Azure VMs, Azure Data Lake Storage Gen2, Azure Blob Storage, and Azure Cosmos DB. You’ll also learn best practices for data lake design and understand when to use relational, NoSQL, and analytical data stores. By the end of this week, you’ll be able to choose appropriate storage and database services based on data type, scale, and access patterns. Week 3 Overview – End-to-End Data Analytics with Azure In Week 3, you’ll dive into analytics solutions using Azure Synapse Analytics, Apache Spark, and Microsoft Fabric. You’ll learn how data stored in Azure can be analyzed using SQL, Spark, and modern analytics tools. This week also introduces Microsoft Fabric, helping you understand modern data platform challenges and unified analytics experiences. By the end of the week, you’ll understand how to build and analyze end-to-end analytics solutions in Azure. Week 4 Overview – Data Ingestion, Monitoring, and Analytics Week 4 focuses on operational aspects of Azure data solutions. You’ll learn how to monitor data platforms using Azure Monitor, track pipelines in Azure Data Factory, and handle ingestion scenarios using Azure Event Hubs and Azure Data Explorer. You’ll also explore Azure Databricks and legacy big data concepts such as HBase on HDInsight for foundational understanding. By the end of this week, you’ll be able to monitor, troubleshoot, and manage Azure data pipelines effectively.
