English | Size: 1.03 GB
Genre: eLearning
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.
Learning ObjectivesGet 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
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