Azure HDinsight Certification Training Course Overview

Enroll for 5-day Azure HDinsight training course from Koenig Solutions.  Azure HDInsight is a managed, full-spectrum, open-source analytics service in the cloud for enterprises. You can use open-source frameworks such as Hadoop, Apache Spark, Apache Hive, LLAP, Apache Kafka, Apache Storm, R, and more.

In this course you will learn to organize HDInsight Clusters and load the data into HDInsight and Troubleshoot HDInsight and as well Analyze Data with Hive, Spark SQL, and Pheonix.

Target Audience:

  • Data Engineers
  • Data Scientists
  • Data Architects
  • Data Developers

Learning Objectives:

After completing this course, you will be able to:

  • Participants will be able to organize HDInsight Clusters and load the data into HDInsight
  • They can Troubleshoot HDInsight and as well Analyze Data with Hive, Spark SQL, and Pheonix
  • Participants will be able to create the Big Data Real-Time Processing Solutions by using Apache Storm and define Stream Analytics.

 

 

Azure HDinsight (40 Hours) Download Course Contents

Live Virtual Classroom
Group Training 3150
18 - 22 Oct 09:00 AM - 05:00 PM CST
(8 Hours/Day)

01 - 05 Nov 09:00 AM - 05:00 PM CST
(8 Hours/Day)

06 - 10 Dec 09:00 AM - 05:00 PM CST
(8 Hours/Day)

1-on-1 Training (GTR) 3650
4 Hours
8 Hours
Week Days
Weekend

Start Time : At any time

12 AM
12 PM

GTR=Guaranteed to Run
Classroom Training (Available: London, Dubai, India, Sydney, Vancouver)
Duration : On Request
Fee : On Request
On Request
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Course Modules

Module 1: Administer and Provision HD Insight Clusters
  • Deploy HDInsight clusters
  • Deploy and secure multi-user HDInsight clusters
  • Ingest data for batch and interactive processing
  • Configure HDInsight clusters
  • Manage and debug HDInsight jobs
Module 2: Implement Big Data Processing Solutions
  • Implement batch solutions with Hive and Apache Pig
  • Design batch ETL solutions: big data with Spark
  • Operationalize Hadoop and Spark
Module 3: Implement Big Data Interactive Processing Solutions
  • Implement interactive queries used for big data with Spark SQL
  • Perform exploratory data analysis by using Spark SQL
  • Implement interactive queries used for big data with Interactive Hive
  • Perform exploratory data analysis by using Hive
  • Perform interactive processing by making use of Apache Phoenix on HBase
Module 4: Implement Big Data Real - Time Processing Solutions
  • Create Spark streaming applications using DStream API
  • Create Spark structured streaming applications
  • Develop the big data real-time processing solutions with Apache Storm
  • Build solutions that use Kafka
  • Build solutions that use HBase
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Course Prerequisites
  • Participants must have strong grasp over Relational databases
  • Basic knowledge of the Microsoft Windows Operating System and its main functionalities.
  • Experience in Programming using R and knowledge of common R packages.
  • Understanding of common statistical techniques and knowledge of the best practices used in Data Analysis is needed