20773 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.
Who Should Attend
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. This course will also help prepare students for one of the exams required to earn the Microsoft Certified Solutions Associate (MCSA): Machine Learning certification.
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
1 - MICROSOFT R SERVER AND R CLIENT
- What is Microsoft R server
- Using Microsoft R client
- The ScaleR functions
- Lab : Exploring Microsoft R Server and Microsoft R Client
2 - EXPLORING BIG DATA
- Understanding ScaleR data sources
- Reading data into an XDF object
- Summarizing data in an XDF object
- Lab : Exploring Big Data
3 - VISUALIZING BIG DATA
- Visualizing In-memory data
- Visualizing big data
- Lab : Visualizing data
4 - PROCESSING BIG DATA
- Transforming Big Data
- Managing datasets
- Lab : Processing big data
5 - PARALLELIZING ANALYSIS OPERATIONS
- Using the RxLocalParallel compute context with rxExec
- Using the revoPemaR package
- Lab : Using rxExec and RevoPemaR to parallelize operations
6 - CREATING AND EVALUATING REGRESSION MODELS
- Clustering Big Data
- Generating regression models and making predictions
- Lab : Creating a linear regression model
7 - CREATING AND EVALUATING PARTITIONING MODELS
- Creating partitioning models based on decision trees.
- Test partitioning models by making and comparing predictions
- Lab : Creating and evaluating partitioning models
8 - PROCESSING BIG DATA IN SQL SERVER AND HADOOP
- Using R in SQL Server
- Using Hadoop Map/Reduce
- Using Hadoop Spark
- Lab : Processing big data in SQL Server and Hadoop
This is a 3-day class
GTR Guaranteed to Run
Class times are listed Eastern time. This class is available for Private Group Training
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