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Introduction to Data Engineering with Microsoft Azure 1

Discover essential data engineering skills and processes within Microsoft Azure services with this online course from Microsoft.

Duration

6 weeks

Weekly study

4 hours

100% online

How it works

Unlimited subscription

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

This course has been created in partnership with Microsoft.

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.

Week 1
Azure for the Data Engineer
- Understand the evolving world of data
  Learn how data systems are evolving and how the changes affect data professionals. Explore the differences between on-premises and cloud data solutions, and consider sample business cases that apply cloud technologies.
- Survey the services on the Azure Data platform
  Learn about Azure technologies that analyze text and images and relational, nonrelational, or streaming data. See how data engineers can choose the technologies that meet their business needs and scale to meet demand securely.
- Identify the tasks of a data engineer in a cloud-hosted architecture
  Learn about the responsibilities of a data engineer. Find out how they relate to the jobs of other data and AI professionals. Explore common data engineering practices.
Week 2
Store data in Azure
- Choose a data storage approach in Azure
  Learn how to use Azure Storage, Azure SQL Database, Azure Cosmos DB, or a combination of Azure resources for a performant solution in your business scenario.
- Create an Azure Storage account
  Create an Azure Storage account with the correct options for your business needs.
- Connect an app to Azure Storage
  Create a simple application and add configuration, client library references, and code to connect it to Azure Storage.
- Secure your Azure Storage account
  Learn how Azure Storage provides multilayered security to protect your data. Find out how to use access keys, to secure networks, and to use Advanced Threat Protection to proactively monitor your system.
- Store application data with Azure Blob storage
  Build an app that stores user files with Azure Blob storage.
Week 3
Data integration at scale with Azure Data Factory or Azure Synapse Pipeline
- Integrate data with Azure Data Factory or Azure Synapse Pipeline
  In this module, you will examine Azure Data Factory and the core components that enable you to create large scale data ingestion solutions in the cloud.
- Petabyte-scale ingestion with Azure Data Factory or Azure Synapse Pipeline
  In this activity, you will learn the various methods that can be used to ingest data between various data stores using Azure Data Factory.
- Perform code-free transformation at scale with Azure Data Factory or Azure Synapse Pipeline
  In this activity, you will learn how to perform common data transformation and cleansing activities within Azure Data Factory without using code.
- Populate slowly changing dimensions in Azure Synapse Analytics pipelines
  In this activity, you will learn how to implement Slowly Changing Dimension using Azure Data Factory or Azure Synapse Pipelines.
- Orchestrate data movement and transformation in Azure Data Factory or Azure Synapse Pipeline
  In this activity, you will learn how Azure Data Factory can orchestrate large scale data movement by using other Azure Data Platform and Machine Learning technologies.
- Execute existing SSIS packages in Azure Data Factory or Azure Synapse Pipeline
  In this activity, you will see how you can integrate SQL Server Integration Services packages into an Azure Data Factory solution.
- Operationalize your Azure Data Factory or Azure Synapse Pipeline
  In this activity, you will learn how you can publish your Azure Data Factory work between different environments.
Week 4
Realize Integrated Analytical Solutions with Azure Synapse Analytics
- Introduction to Azure Synapse Analytics
  Learn the features and components that Azure Synapse Analytics provides to provide a one stop shop for all your analytical needs.
- Survey the Components of Azure Synapse Analytics
  Learn how to recognize and synthesize speech by using Azure Cognitive Services.
- Explore Azure Synapse Studio
  Take a tour of the core application used to interact with the various components of Azure Synapse Analytics.
- Design a Modern Data Warehouse using Azure Synapse Analytics
  Learn how Azure Synapse Analytics enables you to build Data Warehouses using modern architecture patterns.
Week 5
Work with Data Warehouses using Azure Synapse Analytics
- Design a multidimensional schema to optimize analytical workloads
  In this activity, you will study about designing a multidimensional schema to optimize analytical workloads.
- Use data loading best practices in Azure Synapse Analytics
  In this activity, you will learn how to use data loading best practices in Azure Synapse Analytics.
- Optimize data warehouse query performance in Azure Synapse Analytics
  In this activity, you will learn how to optimize data warehouse query performance in Azure Synapse Analytics.
- Integrate SQL and Apache Spark pools in Azure Synapse Analytics
  In this activity, you will learn about integrating SQL and Apache Spark pools in Azure Synapse Analytics.
- Understand data warehouse developer features of Azure Synapse Analytics
  In this activity, you will learn how to understand data warehouse developer features of Azure Synapse Analytics.
- Manage and monitor data warehouse activities in Azure Synapse Analytics
  In this activity, you will learn about managing and monitoring data warehouse activities in Azure Synapse Analytics.
- Analyze and optimize data warehouse storage in Azure Synapse Analytics
  In this activity, you will learn analyze and optimize data warehouse storage in Azure Synapse Analytics.
- Secure a data warehouse in Azure Synapse Analytics
  During this activity, you will learn how to secure a data warehouse in Azure Synapse Analytics.
Week 6
Perform data engineering with Azure Synapse Apache Spark Pools
- Analyze data with Apache Spark in Azure Synapse Analytics
  Apache Spark is a core technology for large-scale data analytics. Learn how to use Spark in Azure Synapse Analytics to analyze and visualize data in a data lake.
- Ingest data with Apache Spark notebooks in Azure Synapse Analytics
  Learn how to ingest data with Apache Spark notebooks in Azure Synapse.
- Transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics
  Learn how to transform data with DataFrames in Apache Spark Pools in Azure Synapse Analytics.
- Integrate SQL and Apache Spark pools in Azure Synapse Analytics
  Learn how to integrate SQL and Apache Spark pools in Azure Synapse Analytics.
- Monitor and manage data engineering workloads with Apache Spark in Azure Synapse Analytics
  Learn how to monitor and manage data engineering workloads with Apache Spark in Azure Synapse Analytics.