Analyzing Big Data with Microsoft R - MOC20773

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Beschreibung

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.

Wir empfehlen den Besuch unserer smart Seminare:

Nach Abschluss dieses Seminars haben die Teilnehmer Wissen zu folgenden Themen:
  • 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

expand_more chevron_right Zielgruppe

Dieses Seminar richtet sich an:
  • 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.

expand_more chevron_right Vorkenntnisse

Für dieses Seminar werden folgende Kenntnisse empfohlen:
  • 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.

expand_more chevron_right Detail-Inhalte

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

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  • Ein guter Kurs, auch für R-Einsteiger. Der Vortragende ist gut auf Fragen eingegangen.

    — Markus S. · 15.05.2019