Big Data Analytics on Azure

Intermediate

LP Box Courses 2 Video Courses
LP Box quiz No quiz sessions
LP Box Lab 2 Hands-on Labs
Duration 2h 29m
Karma ~100 karma points

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.

Learning Objectives

  • 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

Prerequisites

  • Basic database knowledge
  • SQL experience (recommended)
  • Microsoft Azure account (recommended)

Intended Audience

  • Anyone interested in Azure’s big data analytics services

This Learning Path Includes

  • 2 video courses
  • 2 labs
  • 1 exam

Feedback

If you have thoughts or suggestions for this learning path, please contact Cloud Academy at support@cloudacademy.com.

Updates

April 10th 2018 - Lab added - Submitting a U-SQL Job to Azure Data Lake Analytics  

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1

Course Description Azure Data Lake Store (ADLS) is a cloud-based repository for both structured and unstructured data. For example, you could use it to store everything from documents to images to social media streams. ADLS is designed for big data analytics in a Hadoop environment. It is compatible with Hadoop Distributed File System (HDFS), so you can run your existing Hadoop jobs by simply ...

2

Lab Overview Big data and analytics in Azure can help you gain insights into your data and deliver better experiences. This Lab demonstrates using two of Azure's big data services: Azure Data Lake Store for storing massive amounts of structured, semi-structured, and unstructured data, and Azure Data Lake Analytics for massively parallel analysis of data stored in Data Lake Store. You will use ...

3

Course Description 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. Although these tasks could be performed in batch jobs once a day, they are much more valuable if they run in real time. For example, if you can detect credit card fraud ...

4

Lab Overview Azure Stream Analytics is a fully-managed service for analyzing real-time streaming data. A common use case for Stream Analytics is analyzing Internet of Things (IoT) device data. Stream Analytics accepts streaming input data sources from a variety of sources in Azure, including IoT Hubs. In this Lab, you will develop a Stream Analytics query that analyzes Internet of Things (IoT) ...

5

OverviewThis exam will test the concepts, services and methods discussed in the Big Data Analytics on Azure learning path. You have 20 minutes to complete 20 multiple choice questions. You must score 60 percent or higher to pass this exam.Questions will focus on the following topics:Azure Data Lake StoreAzure Data Lake AnalyticsAzure Strem AnalyticsOnce you begin your exam session:You can spend ...
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