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Analyzing Big Data with Microsoft R (MOC-20773)

MOC-20773 (3 Days)

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Analyzing Big Data with Microsoft R Training Overview

This Microsoft course 20773, Analyzing Big Data with Microsoft R training, teaches participants how to use Microsoft R Server to create and run analyses on large datasets and utilize them in Big Data environments, including Hadoop, Spark, and SQL Server 2016.

Location and Pricing

Most Accelebrate courses are delivered as private, customized, on-site training at our clients' locations worldwide for groups of 3 or more attendees and are custom tailored to their specific needs. Please visit our client list to see organizations for whom we have delivered private in-house training. These courses can also be delivered as live, private online classes for groups that are geographically dispersed or wish to save on the instructor's or students' travel expenses. To receive a customized proposal and price quote for private training at your site or online, please contact us.

Analyzing Big Data with Microsoft R Training Objectives

All 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

Analyzing Big Data with Microsoft R Training Outline

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Introduction
Microsoft R Server and R Client
  • What is Microsoft R server
  • Using Microsoft R client
  • The ScaleR functions
Exploring Big Data
  • Understanding ScaleR data sources
  • Reading data into an XDF object
  • Summarizing data in an XDF object
Visualizing Big Data
  • Visualizing In-memory data
  • Visualizing big data
Processing Big Data
  • Transforming Big Data
  • Managing datasets
Parallelizing Analysis Operations
  • Using the RxLocalParallel compute context with rxExec
  • Using the revoPemaR package
Creating and Evaluating Regression Models
  • Clustering Big Data
  • Generating regression models and making predictions
Creating and Evaluating Partitioning Models
  • Creating partitioning models based on decision trees.
  • Test partitioning models by making and comparing predictions
Processing Big Data in SQL Server and Hadoop
  • Using R in SQL Server
  • Using Hadoop Map/Reduce
  • Using Hadoop Spark
Conclusion
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Lecture percentage

50%

Lecture/Demo

Lab percentage

50%

Lab

Course Number:

MOC-20773

Duration:

3 Days

Prerequisites:

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.

Training Materials:

All Microsoft training students receive Microsoft official courseware.

Software Requirements:

Attendees will not need to install any software on their computer for this class. The class will be conducted in a remote environment that Accelebrate will provide; students will only need a local computer with a web browser with a stable Internet connection. Any recent version of Internet Explorer, Mozilla Firefox, or Google Chrome will be fine.

When you call us about purchasing this class, we will provide a live demo of the online lab environment so that you may explore the web browser interface in more detail.

Contact Us:

Accelebrate’s training classes are available for private groups of 3 or more people at your site or online anywhere worldwide.

Don't settle for a "one size fits all" public class! Have Accelebrate deliver exactly the training you want, privately at your site or online, for less than the cost of a public class.

For pricing and to learn more, please contact us.

Contact Us Train For Us

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International:
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Toll-free in US/Canada:
866 566 1228
International:
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