MOC On-Demand Packaged Set 20773A: Analyzing Big Data with Microsoft R (180 Day) (Q4P-00325)
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.
Microsoft On Demand
Microsoft Official Courses On-Demand (MOC On-Demand) blend video, text, hands-on labs and knowledge checks to help you build your Microsoft technology skills on your own schedule, at your own pace and in your own place. No need to spend time and money travelling to a classroom location or adhering to classroom hours with a computer and an Internet connection, your Microsoft Official Courses On-Demand come to you, any time.
Microsoft On Demand Packaged Set
Including
Audience Profile
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.
Prerequisites
In addition to their professional experience, students who attend this course should have:
Show details
Microsoft On Demand
Microsoft Official Courses On-Demand (MOC On-Demand) blend video, text, hands-on labs and knowledge checks to help you build your Microsoft technology skills on your own schedule, at your own pace and in your own place. No need to spend time and money travelling to a classroom location or adhering to classroom hours with a computer and an Internet connection, your Microsoft Official Courses On-Demand come to you, any time.
- Microsoft On Demand covers the same objectives as the classroom course by the same name
- After you activate your course, you have 6 months to complete it. You can work on your course at any time throughout the 6-month period after you activate the course.
Microsoft On Demand Packaged Set
Including
- Microsoft On Demand Course ODX20773A (includes Microsoft Labs Online)
- Digital courseware Course 20773A
Audience Profile
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.
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.
Working knowledge of relational databases.
Objectives
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
Course Outline
Module 1: Microsoft R Server and R Client
Explain how Microsoft R Server and Microsoft R Client work.
Lessons
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.
Lessons
Module 3: Visualizing Big Data
Explain how to visualize data by using graphs and plots.
Lessons
Module 4: Processing Big Data
Explain how to transform and clean big data sets.
Lessons
Module 5: Parallelizing Analysis Operations
Explain how to implement options for splitting analysis jobs into parallel tasks.
Lessons
Module 6: Creating and Evaluating Regression Models
Explain how to build and evaluate regression models generated from big data
Lessons
Module 7: Creating and Evaluating Partitioning Models
Explain how to create and score partitioning models generated from big data.
Lessons
Module 8: Processing Big Data in SQL Server and Hadoop
Explain how to transform and clean big data sets.
Lessons
Module 1: Microsoft R Server and R Client
Explain how Microsoft R Server and Microsoft R Client work.
Lessons
- What is Microsoft R server
- Using Microsoft R client
- The ScaleR functions
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.
Lessons
- Understanding ScaleR data sources
- Reading data into an XDF object
- Summarizing data in an XDF object
Module 3: Visualizing Big Data
Explain how to visualize data by using graphs and plots.
Lessons
- Visualizing In-memory data
- Visualizing big data
Module 4: Processing Big Data
Explain how to transform and clean big data sets.
Lessons
- Transforming Big Data
- Managing datasets
Module 5: Parallelizing Analysis Operations
Explain how to implement options for splitting analysis jobs into parallel tasks.
Lessons
- Using the RxLocalParallel compute context with rxExec
- Using the revoPemaR package
Module 6: Creating and Evaluating Regression Models
Explain how to build and evaluate regression models generated from big data
Lessons
- Clustering Big Data
- Generating regression models and making predictions
Module 7: Creating and Evaluating Partitioning Models
Explain how to create and score partitioning models generated from big data.
Lessons
- Creating partitioning models based on decision trees.
- Test partitioning models by making and comparing predictions
Module 8: Processing Big Data in SQL Server and Hadoop
Explain how to transform and clean big data sets.
Lessons
- Using R in SQL Server
- Using Hadoop Map/Reduce
- Using Hadoop Spark
