Wir beraten Sie gerne!
+41 44 832 50 80     Kontakt

Online-Trainings im virtuellen Klassenraum,
E-Learning-Angebote und mehr

Jetzt informieren

Analyzing Big Data with Microsoft R (MOC 20773)

Detaillierter Kursinhalt

Module 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

  • Using R client in VSTR and RStudio
  • Exploring ScaleR functions
  • Connecting to a remote server

Module 2: Exploring Big Data

  • 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

Module 3: Visualizing Big Data

  • Visualizing In-memory data
  • Visualizing big data

Lab : Visualizing data

  • Using ggplot to create a faceted plot with overlays
  • Using rxlinePlot and rxHistogram

Module 4: Processing Big Data

  • Transforming Big Data
  • Managing datasets

Lab : Processing big data

  • Transforming big data
  • Sorting and merging big data
  • Connecting to a remote server

Module 5: Parallelizing Analysis Operations

  • Using the RxLocalParallel compute context with rxExec
  • Using the revoPemaR package

Lab : Using rxExec and RevoPemaR to parallelize operations

  • Using rxExec to maximize resource use
  • Creating and using a PEMA class

Module 6: Creating and Evaluating Regression Models

  • Clustering Big Data
  • Generating regression models and making predictions

Lab : Creating a linear regression model

  • Creating a cluster
  • Creating a regression model
  • Generate data for making predictions
  • Use the models to make predictions and compare the results

Module 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

  • Splitting the dataset
  • Building models
  • Running predictions and testing the results
  • Comparing results

Module 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

  • Creating a model and predicting outcomes in SQL Server
  • Performing an analysis and plotting the results using Hadoop Map/Reduce
  • Integrating a sparklyr script into a ScaleR workflow