In this course, the student will learn how to implement and manage data engineering workloads on Microsoft Azure, using Azure services such as Azure Synapse Analytics, Azure Data Lake Storage Gen2, Azure Stream Analytics, Azure Databricks, and others. The course focuses on common data engineering tasks such as orchestrating data transfer and transformation pipelines, working with data files in a data lake, creating and loading relational data warehouses, capturing and aggregating streams of real-time data, and tracking data assets and lineage.

Audience Profile:
The primary audience for this course is data professionals, data architects, and business intelligence professionals who want to learn about data engineering and building analytical solutions using data platform technologies that exist on Microsoft Azure. The secondary audience for this course includes data analysts and data scientists who work with analytical solutions built on Microsoft Azure.

• Get started with data engineering on Azure
• Build data analytics solutions using Azure Synapse serverless SQL pools
• Perform data engineering with Azure Synapse Apache Spark Pools
• Work with Data Warehouses using Azure Synapse Analytics
• Transfer and transform data with Azure Synapse Analytics pipelines
• Work with Hybrid Transactional and Analytical Processing Solutions using Azure Synapse Analytics
• Implement a Data Streaming Solution with Azure Stream Analytics
• Govern data across an enterprise
• Implement a Data Analytics Solution with Azure Databricks

• Payment in cash with payment slip or debit cards
• Payment in installments with credit cards
• Payment in installments without interest with credit cards of Stopanska Banka
• Payment by invoice