Learning Path Description
Microsoft Azure provides robust services for analyzing big data. One of the most effective ways is to store your data in Azure Data Lake Storage Gen2 and then process it using Spark on Azure Databricks.
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.
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 Stream Analytics 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 Azure Data Lake Storage (ADLS)
- Use six layers of security to protect data in ADLS
- Use Azure Databricks to process data in ADLS
- Monitor and optimize the performance of your data lakes
- 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
If you have thoughts or suggestions for this learning path, please contact Cloud Academy at firstname.lastname@example.org.
Learning Path Steps
In this course, we will show you how to set up a Databricks cluster and run interactive queries and Spark jobs on it.
In this course, you will follow hands-on examples to import data into Azure Data Lake Storage Gen2 and then securely access it and analyze it using Azure Databricks. You will also learn how to monitor and optimize your Azure Data Lake Storage Gen2.
Learn to implement lightning-fast analytics by building an Azure Databricks workspace and cluster to interact with Azure Data Lake Store data.
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.
Final 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).