Introduction to Data Engineering with Microsoft Azure 2

Prepare for the DP-203: Data Engineering on Microsoft Azure exam

Building on your learning from Introduction to Data Engineering with Microsoft Azure 1, this course will develop your understanding of data engineering processes in Microsoft Azure, further preparing you to take the DP-203 exam and kickstart your career in data engineering.

Explore data services within Microsoft Azure

Using Azure data services and tools, you’ll be able to implement, develop, and optimise data storage, processing and security operations within your organisation.

You’ll be introduced to tools including Azure Synapse, Databricks and Azure Data Lake Storage, learning how each can improve and streamline your processes.

Design hybrid transactional and analytical processing (HTAP) patterns

As businesses continue to move to digital processes, they recognise the value of making faster, well-informed decisions and the impact this can have on gaining a competitive advantage.

You’ll be guided through HTAP architecture and learn how to design HTAP using Azure Synapse Analytics.

With this knowledge, you’ll be able to run analytics in near-real-time, giving you the ability to respond to opportunities at speed.

Discover data operations in Azure Databricks

Azure Databricks, a cloud-based big data and machine learning platform, empowers developers by simplifying enterprise-grade data application production.

You’ll identify the advantages of Azure Databricks over other Big Data platforms, and learn how to spend more time building apps and less time managing infrastructure.

You’ll finish this course understanding how Microsoft Azure can be used to optimise data engineering operations. Having completed both courses, you’ll be equipped to take the DP-203 exam and develop a career as a data professional.

This course is designed for data professionals preparing for the DP 203: Data Engineering on Microsoft Azure exam.

Before taking this course, learners should take Introduction to Data Engineering with Microsoft Azure 1 to ensure they have covered all topics required for the DP 203 exam.

It’s recommended that you already have a solid understanding of data processing languages, as well as parallel processing and data architecture patterns before taking the exam.

• Work with Hybrid Transactional and Analytical Processing Solutions using Azure Synapse Analytics
• Plan hybrid transactional and analytical processing using Azure Synapse Analytics
• Configure Azure Synapse Link with Azure Cosmos DB
• Query Azure Cosmos DB with Apache Spark for Azure Synapse Analytics
• Query Azure Cosmos DB with SQL Serverless for Azure Synapse Analytics
• Data engineering with Azure Databricks Part 1
• Describe Azure Databricks
• Spark architecture fundamentals
• Read and write data in Azure Databricks
• Work with DataFrames in Azure Databricks
• Work with DataFrames columns in Azure Databricks
• Data engineering with Azure Databricks Part 2
• Describe lazy evaluation and other performance features in Azure Databricks
• Work with DataFrames advanced methods in Azure Databricks
• Describe platform architecture, security, and data protection in Azure Databricks
• Build and query a Delta Lake
• Process streaming data with Azure Databricks structured streaming
• Data engineering with Azure Databricks Part 3
• Describe Azure Databricks Delta Lake architecture
• Create production workloads on Azure Databricks with Azure Data Factory
• Implement CI/CD with Azure DevOps
• Integrate Azure Databricks with Azure Synapse
• Describe Azure Databricks best practices
• Large-Scale Data Processing with Azure Data Lake Storage Gen2
• Introduction to Azure Data Lake storage
• Upload data to Azure Data Lake Storage
• Secure your Azure Storage account
• Implement a Data Streaming Solution with Azure Streaming Analytics
• Work with data streams by using Azure Stream Analytics
• Enable reliable messaging for Big Data applications using Azure Event Hubs
• Ingest data streams with Azure Stream Analytics