Analyzing Big Data with Microsoft R
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.
The primary audience for this course is people who wish to analyze large datasets within a big data environment
The secondary audience is developers who need to integrate R analyses into their solutions
After completing this course, students will be able to:
Explain how Microsoft R Server and Microsoft R Client work
Use R Client with R Server to explore big data held in different data stores
Visualize data by using graphs and plots
Transform and clean big data sets
Implement options for splitting analysis jobs into parallel tasks
Build and evaluate regression models generated from big data
Create, score, and deploy partitioning models generated from big data
Use R in the SQL Server and Hadoop environments
In addition to their professional experience, students who attend this course should have:
Programming experience using R, and familiarity with common R packages
Knowledge of common statistical methods and data analysis best practices.
Basic knowledge of the Microsoft Windows operating system and its core functionality.
Candidates for this exam are data scientists or analysts who process and analyse data sets larger than memory using R. Candidates should have experience with R, familiarity with data structures, familiarity with basic programming concepts (such as control flow and scope), and familiarity with writing and debugging R functions.
Candidates should be familiar with common statistical methods and data analysis best practices. Candidates should also have a high-level understanding of data platforms, such as the Hadoop ecosystem, SQL Server, and core T-SQL capabilities.