In this course, you’ll learn key concepts of working with data in the cloud, such as common data formats, workloads, roles, and services. You’ll study relational databases to build new applications and migrate existing ones to the cloud. You’ll also learn to manage non-relational databases by using Azure Storage and Azure Cosmos DB to build highly scalable and secure data stores.
In addition, you’ll learn to use multiple technologies available in Microsoft Azure to build a modern data warehousing solution. Finally, you’ll learn the basics of stream processing and the services in Microsoft Azure you can use to implement real-time analytics solutions.
Best of all, you’ll learn by doing — you’ll practice and get feedback directly in the browser.
- Using core data concepts in the cloud
- Manipulating relational and non-relational databases in Azure
- Implementing real-time data analytics in Azure
- Building data visualizations in Power BI
Introduction to Cloud Data with Microsoft Azure [9 lessons]
Introduction to Microsoft Azure 2hLesson Objectives
- Describe the basic concepts of cloud computing
- Identify common data formats
- Determine options for storing data in files
- Navigate the Azure Portal
Core Data Concepts 2hLesson Objectives
- Understand relational and non-relational data
- Apply the concept of normalization by joining data together
- Use SQL SELECT statements to explore databases
- Describe database objects
Relational Data in Azure 2hLesson Objectives
- Describe Azure SQL services and capabilities
- Describe Azure services for open-source databases
- Provision an Azure relational database service
- Query an Azure SQL database resource
Non-Relational Data in Azure 2hLesson Objectives
- Set up Azure blob storage
- Upgrade to Azure Data Lake Storage Gen2
- Use file share, noSQL tables, and storage accounts in Azure
Fundamentals of Azure Cosmos DB 2hLesson Objectives
- Describe and explore Azure Cosmos DB
- Identify the APIs supported in Azure Cosmos DB
- Provision and use an Azure Cosmos DB instance
- Query a database using the Core (SQL) API
Data Warehousing in Azure 2hLesson Objectives
- Describe characteristics of transactional and analytical data processing solutions
- Explore data warehousing and data ingestion pipelines
- Explore analytical data stores using Azure Synapse Analytics
- Run Python code in a Spark pool
Real-time Data Analytics in Azure - I 2hLesson Objectives
- Understand batch and stream processing
- Explore common elements of stream processing architecture
- Explore Azure Stream Analytics
- Explore Apache Spark on Microsoft Azure
Real-time Data Analytics in Azure - II 2hLesson Objectives
- Process streaming data using Spark
- Create a Spark Pool and explore stream processing
- Create a Data Explorer Pool
- Query a table in Synapse Studio using Kusto Query Language
Data visualization with Power BI 2hLesson Objectives
- Describe Power BI tools and workflow
- Describe core concepts of data modeling
- Describe considerations for data visualization
- Visualize data with Power BI
- Identify common data professional roles
The Dataquest guarantee
Dataquest has helped thousands of people start new careers in data. If you put in the work and follow our path, you’ll master data skills and grow your career.
We believe so strongly in our paths that we offer a full satisfaction guarantee. If you complete a career path on Dataquest and aren’t satisfied with your outcome, we’ll give you a refund.
Master skills faster with Dataquest
Go from zero to job-ready
Learn exactly what you need to achieve your goal. Don’t waste time on unrelated lessons.
Build your project portfolio
Build confidence with our in-depth projects, and show off your data skills.
Challenge yourself with exercises
Work with real data from day one with interactive lessons and hands-on exercises.
Showcase your path certification
Impress employers by completing a capstone project and certifying it with an expert review.