Performing Data Engineering on Microsoft HD Insight

The main purpose of the course is to give students the ability plan and implement big data workflows on HDInsight.

Audience profile:

The primary audience for this course is data engineers, data architects, data scientists, and data developers who plan to implement big data engineering workflows on HDInsight.

At course completion:

After completing this course, students will be able to:

• Deploy HDInsight Clusters.
• Authorizing Users to Access Resources. 
• Loading Data into HDInsight.
• Troubleshooting HDInsight. 
• Implement Batch Solutions.
• Design Batch ETL Solutions for Big Data with Spark 
• Analyze Data with Spark SQL.
• Analyze Data with Hive and Phoenix. 
• Describe Stream Analytics.
• Implement Spark Streaming Using the DStream API.
• Develop Big Data Real-Time Processing Solutions with Apache Storm.
• Build Solutions that use Kafka and HBase.

Course Outline:

Module 1: Getting Started with HDInsight
Module 2: Deploying HDInsight Clusters
Module 3: Authorizing Users to Access Resources
Module 4: Loading data into HDInsight
Module 5: Troubleshooting HDInsight
Module 6: Implementing Batch Solutions
Module 7: Design Batch ETL solutions for big data with Spark
Module 8: Analyze Data with Spark SQL
Module 9: Analyze Data with Hive and Phoenix
Module 10: Stream Analytics
Module 11: Implementing Streaming Solutions with Kafka and HBase
Module 12: Develop big data real-time processing solutions with Apache Storm
Module 13: Create Spark Streaming Applications