MOC On-Demand: 20773-Analyzing Big Data with Microsoft R - On-Demand Course

  The Analyzing Big Data with Microsoft R - 20773 course is a 3-day course that is designed to teach students how to use Microsoft R Server to create and run an analysis on large datasets. The course will also show students how to utilize R Server in Big Data environments, such as a Hadoop or Spark cluster, or a SQL Server database

Topics covered in the course include:

• 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

Target Student: This course is designed for students who want to analyze large datasets within a big data environment, or for developers than want to integrate R analyses into their solutions. Students should have R programming experinece and be familiar with common R packages. Students should also have knowledge of statistical methods, data analysis best practices and the Window operating system.

Section 1: Microsoft R Server and R Client
This section discusses how Microsoft R Server and Microsoft R Client work.
Topics :
• What is Microsoft R server
• Working with Microsoft R client
• The ScaleR functions
Lab : Exploring Microsoft R Server and Microsoft R Client
• Working with R client in VSTR and RStudio
• Exploring ScaleR functions
• Connecting to a remote server

Section 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.
Topics :
• Understanding ScaleR data sources
• Reading data into an XDF object
• Summarizing data in an XDF object
Lab : Exploring Big Data
• Reading a local CSV file into an XDF file
• Transforming data on input
• Reading data from SQL Server into an XDF file
• Generating summaries over the XDF data

Section 3: Visualizing Big Data
This section discusses how to visualize data by Working with graphs and plots.
Topics :
• Visualizing In-memory data
• Visualizing big data
Lab : Visualizing data
• Working with ggplot to create a faceted plot with overlays
• Working with rxlinePlot and rxHistogram

Section 4: Processing Big Data
This section discusses how to transform and clean big data sets.
Topics :
• Transforming Big Data
• Managing datasets
Lab : Processing big data
• Transforming big data
• Sorting and merging big data
• Connecting to a remote server

Section 5: Parallelizing Analysis Operations
This section discusses how to implement options for splitting analysis jobs into parallel tasks.
Topics :
• Working with the RxLocalParallel compute context with rxExec
• Working with the revoPemaR package
Lab : Working with rxExec and RevoPemaR to parallelize operations
• Working with rxExec to maximize resource use
• Create and Working with a PEMA class

Section 6: Create and Evaluating Regression Models
This section discusses how to build and evaluate regression models generated from big data
Topics :
• Clustering Big Data
• Generating regression models and making predictions
Lab : Create a linear regression model
• Create a cluster
• Create a regression model
• Generate data for making predictions
• Use the models to make predictions and compare the results

Section 7: Create and Evaluating Partitioning Models
This section discusses how to create and score partitioning models generated from big data.
Topics :
• Create partitioning models based on decision trees.
• Test partitioning models by making and comparing predictions
Lab : Create and evaluating partitioning models
• Splitting the dataset
• Building models
• Running predictions and testing the results
• Comparing results

Section 8: Processing Big Data in SQL Server and Hadoop
This section discusses how to transform and clean big data sets.
Topics :
• Working with R in SQL Server
• Working with Hadoop Map/Reduce
• Working with Hadoop Spark
Lab : Processing big data in SQL Server and Hadoop
• Create a model and predicting outcomes in SQL Server
• Perform an analysis and plotting the results Working with Hadoop Map/Reduce
• Integrate a sparklyr script into a ScaleR workflow