Data Engineering and Analytics on Microsoft Cloud – Azure

Description:

This training focuses on the powerful data engineering and analytics capabilities provided by Microsoft Azure. Participants will learn how to build robust data pipelines, process large datasets, and perform analytics using Azure services. The training includes an introduction to key Azure tools like Data Factory, Synapse Analytics, and Databricks, complemented by hands-on exercises to apply concepts in real-world scenarios. By the end of the day, participants will have the confidence to implement scalable data engineering and analytics workflows on Azure.

Duration: 1 Day

Course Code: BDT32

Learning Objectives:

By the end of this training, participants will be able to:

• Describe the data engineering and analytics services available on Azure.
• Build data pipelines using Azure Data Factory.
• Process and analyze data with Azure Synapse Analytics and Azure Databricks.
• Design scalable workflows for ETL and data integration.
• Evaluate use cases for applying Azure solutions in analytics.

• Basic understanding of data concepts, including ETL and analytics, is recommended. Familiarity with cloud platforms is helpful but not required.

• Data engineers and analysts exploring Azure solutions.
• IT professionals seeking to integrate data workflows on Azure.
• Business professionals interested in leveraging data analytics on the cloud.

Course Outline:

Module 1: Introduction to Data Engineering and Analytics on Azure

• Overview of Data Engineering and Analytics Concepts
• Introduction to Azure’s Data Ecosystem
• Key Services: Azure Data Factory, Synapse Analytics, Databricks

Module 2: Building Data Pipelines with Azure Data Factory

• Introduction to Azure Data Factory (ADF)
• Data Integration and ETL Workflow Design
• Hands-On: Creating and Managing Pipelines

Module 3: Processing and Analyzing Data with Azure Synapse Analytics

• Overview of Azure Synapse: Features and Architecture
• Performing Analytics with SQL and Serverless Pools
• Hands-On: Analyzing Data in Synapse

Module 4: Advanced Data Processing with Azure Databricks

• Introduction to Azure Databricks and Apache Spark Integration
• Processing Large Datasets in Real-Time
• Hands-On: Implementing Analytics with Databricks

Module 5: Real-World Use Cases and Wrap-Up

• Real-World Applications of Data Engineering on Azure
• Best Practices for Performance and Cost Optimization
• Q&A and Additional Resources

Training material provided: Yes (Digital format)