Technology: SQL Server
Software Assurance Value:
The main purpose of the course is to give students the ability to use Microsoft R Server to create and run an analysis on a large dataset, and show how to utilize it in Big Data environments, such as a Hadoop or Spark cluster, or a SQL Server database.
After completing this course, students will be able to:
The primary audience for this course is people who wish to analyze large datasets within a big data environment.
The secondary audience are developers who need to integrate R analyses into their solutions.
Module 1: Microsoft R Server and R Client
Explain how Microsoft R Server and Microsoft R Client work.
Lab : Exploring Microsoft R Server and Microsoft R Client
After completing this module, students will be able to:
Module 2: Exploring Big Data
At the end of this module the student will be able to use R Client with R Server to explore big data held in different data stores.
Lab : Exploring Big Data
Module 3: Visualizing Big DataExplain how to visualize data by using graphs and plots.
Lab : Visualizing data
Module 4: Processing Big Data
Explain how to transform and clean big data sets.
Lab : Processing big data
Module 5: Parallelizing Analysis Operations
Explain how to implement options for splitting analysis jobs into parallel tasks.
Lab : Using rxExec and RevoPemaR to parallelize operations
Module 6: Creating and Evaluating Regression Models
Explain how to build and evaluate regression models generated from big data
Lab : Creating a linear regression model
Module 7: Creating and Evaluating Partitioning Models
Explain how to create and score partitioning models generated from big data.
Lab : Creating and evaluating partitioning models
Module 8: Processing Big Data in SQL Server and Hadoop
Lab : Processing big data in SQL Server and Hadoop
In addition to their professional experience, students who attend this course should have: