Learning Path Description
Microsoft Azure provides robust services for analyzing big data. Azure Data Lake Analytics (ADLA) lets you analyze both structured and unstructured data Azure Data Lake Store (ADLS) using a language called U-SQL that brings together the benefits of SQL and C#. Although it’s possible to run Hadoop MapReduce-based analytics jobs on ADL Store, U-SQL is much easier to use.
Azure Stream Analytics (ASA) is Microsoft’s service for real-time data analytics. Some examples include stock trading analysis, fraud detection, embedded sensor analysis, and web clickstream analytics. ASA uses Stream Analytics Query Language, which is a variant of T-SQL. That means anyone who knows SQL will have a fairly easy time learning how to write jobs for Stream Analytics. That’s not the case with alternative software, such as Apache Spark or Storm.
In this learning path, you will follow hands-on examples to import data, run queries, and output the results using both analytics services. You will also learn how to troubleshoot processing jobs. Then you will have the opportunity to run a Stream Analytics job yourself with our guided, hands-on lab. Finally, you can take our exam to test your understanding of what you learned.
- Get data into and out of ADL Store
- Use the five layers of security to protect data in ADL Store
- Use ADL Analytics to process data in a data lake
- Troubleshoot errors in ADL Analytics jobs
- Create and run a Stream Analytics job
- Use time windows to process streaming data
- Scale a Stream Analytics job
- Monitor and troubleshoot errors in Stream Analytics jobs
- Basic database knowledge
- SQL experience (recommended)
- Microsoft Azure account (recommended)
- Anyone interested in Azure’s big data analytics services
This Learning Path Includes
- 2 video courses
- 2 labs
- 1 exam
If you have thoughts or suggestions for this learning path, please contact Cloud Academy at firstname.lastname@example.org.
April 10th 2018 - Lab added - Submitting a U-SQL Job to Azure Data Lake Analytics
Learning Path Steps
In this course, you'll learn how to store and process big data with Azure Data Lake Store and Azure Data Lake Analytics, and follow hands-on examples of big data analytics and troubleshooting.
Develop your Azure big data skills by creating an Azure Data Lake Analytics job to analyze data in an Azure Data Lake Store using a U-SQL script
This course includes hands-on examples of how to configure inputs, outputs, and queries in ASA jobs, including ingesting data from Event Hubs and writing results to Data Lake Store.
Analyze Internet of Things (IoT) sensor data using Azure Stream Analytics to identify if there have been any IoT device failures in this Lab.
Exam: Big Data Analytics on Azure
About the Author
Guy launched his first training website in 1995 and he's been helping people learn IT technologies ever since. He has been a sysadmin, instructor, sales engineer, IT manager, and entrepreneur. In his most recent venture, he founded and led a cloud-based training infrastructure company that provided virtual labs for some of the largest software vendors in the world. Guy’s passion is making complex technology easy to understand. His activities outside of work have included riding an elephant and skydiving (although not at the same time).