Introduction to Data Engineering with Microsoft Azure 1

Gain the skills to pass the DP-203: Data Engineering on Microsoft Azure exam

Over recent years, the data generated by systems and devices has increased massively.

On this course, you’ll explore the generation, storage, and management of data using various technologies and platforms and prepare to take the DP-203 exam.

Learn the fundamentals of Azure for the data engineer

Data professionals must understand the evolving data landscape and the roles and technologies that have changed with it.

You’ll investigate data platforms, including cloud technologies, and examine a data engineer’s role in helping organizations benefit from technological advances.

Improve data integration using Azure Synapse Analytics

A data engineer’s responsibilities include building and maintaining secure data processing pipelines, and explaining these processes to stakeholders.

Using Azure Data Factory and Azure Synapse Pipeline, you’ll learn to manage data pipelines and build analytical solutions that align with business requirements.

Identify new organizational opportunities using emerging technologies

Using tools such as Apache Spark, you’ll be able to boost the performance of big-data analytic applications, taking your data visualization and analysis skills to the next level.

With a range of exercises aimed to get you comfortable working across Azure’s suite, you’ll finish this course able to optimize, monitor, and manage your data engineering workload, whatever the scale.

By the end of this course, you’ll have gained the introductory knowledge in preparation for the DP 203 exam. By continuing your learning with Introduction to Data Engineering with Microsoft Azure 2, you’ll equip yourself with all the necessary knowledge to pass the exam and progress your career in data engineering.

This course is designed for data professionals who want to prepare for the DP 203: Data Engineering on Microsoft Azure exam.

Learners should follow this course with Introduction to Data Engineering with Microsoft Azure 2, to ensure they have all the knowledge required to take 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.

• Azure for the Data Engineer
• Understand the evolving world of data
• Survey the services on the Azure Data platform
• Identify the tasks of a data engineer in a cloud-hosted architecture
• Store data in Azure
• Choose a data storage approach in Azure
• Create an Azure Storage account
• Connect an app to Azure Storage
• Secure your Azure Storage account
• Store application data with Azure Blob storage
• Data integration at scale with Azure Data Factory or Azure Synapse Pipeline
• Integrate data with Azure Data Factory or Azure Synapse Pipeline
• Petabyte-scale ingestion with Azure Data Factory or Azure Synapse Pipeline
• Perform code-free transformation at scale with Azure Data Factory or Azure Synapse Pipeline
• Populate slowly changing dimensions in Azure Synapse Analytics pipelines
• Orchestrate data movement and transformation in Azure Data Factory or Azure Synapse Pipeline
• Execute existing SSIS packages in Azure Data Factory or Azure Synapse Pipeline
• Operationalize your Azure Data Factory or Azure Synapse Pipeline
• Realize Integrated Analytical Solutions with Azure Synapse Analytics
• Introduction to Azure Synapse Analytics
• Survey the Components of Azure Synapse Analytics
• Explore Azure Synapse Studio
• Design a Modern Data Warehouse using Azure Synapse Analytics
• Work with Data Warehouses using Azure Synapse Analytics
• Design a multidimensional schema to optimize analytical workloads
• Use data loading best practices in Azure Synapse Analytics
• Optimize data warehouse query performance in Azure Synapse Analytics
• Integrate SQL and Apache Spark pools in Azure Synapse Analytics
• Understand data warehouse developer features of Azure Synapse Analytics
• Manage and monitor data warehouse activities in Azure Synapse Analytics
• Analyze and optimize data warehouse storage in Azure Synapse Analytics
• Secure a data warehouse in Azure Synapse Analytics
• Perform data engineering with Azure Synapse Apache Spark Pools
• Analyze data with Apache Spark in Azure Synapse Analytics
• Ingest data with Apache Spark notebooks in Azure Synapse Analytics
• Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics
• Integrate SQL and Apache Spark pools in Azure Synapse Analytics
• Monitor and manage data engineering workloads with Apache Spark in Azure Synapse Analytics