Greens Technology
15 First Street Padmanabha Nagar, Adyar, Chennai
      Greens Technology Contact
Email: contact@greenstechnologys.com

Data Mining with Statistics

Integrated Course Outline

Base SAS

  • Navigate the SAS windowing environment
  • Read various types of data into SAS data sets
  • Validate and clean SAS data sets
  • Create SAS variables and subset data
  • Combine SAS data sets
  • Crete and enhance listing and summary reports
  • Control SAS data set input and output
  • Combine SAS data sets
  • Summarize,read,and write different types of data
  • Perform DO loop and SAS array processing
  • Transform character , numeric,and date variables

Creating Business Intelligence using SAS Reports

  • Use several of the business user applications in the platform for SAS Business Analytics
  • Create and Exploit dynamic value selection
  • Build advanced information maps using SAS Information Map Studio
  • Create advanced SAS BI Dashboard applications
  • Produce advanced stored processes able to create dynamic data sources
  • Build,schedule,and distribute advanced reports
  • Consolidate information into a business reporting application
  • Describe the online analytical processing capabilities available in the SAS platform
  • Explore the basic functionality of the SAS integration with JMP
  • Examine the types of metadata created in the SAS platform

SAS Analytics (SAS Enterprise Guide :ANOVA Regression & Logistic Regression , Applied Analytics using SAS Enterprise Miner)

  • Generate descriptives statistics and explore data with graphs
  • Perform analysis of variance
  • Perform linear regression and assess the assumptions
  • Use diagnostic statistics to identify potential outliers in multiple regression
  • Use chi-square statistics to detect associations among categorical variables
  • Fit a multiple logistics regression mode
  • Define a SAS Enterprise Miner project and explore data graphically
  • Modify data for better analysis results
  • Build and understand predictive models such as decision trees and regression models
  • Compare and explain complex models
  • Generate and use score code
  • Apply association and sequence discovery to transaction data
  • Use other modeling tools such as rule induction ,gradient boosting ,and support vector machines




  • Dinesh J
    CEO, Greens Technology
    Trainer, Exp: 12 yrs
    Mobile: +91 8939915577
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