Setup Menus in Admin Panel

Hi, I’m Anna Rakers for The SAS Academy for Data Science. Welcome to the Big Data Preparation, Statistics and Visual Exploration learning module.

SAS gives you the power to know, and training enables you to harness that power. Since 1999, the SAS Global Certification program has helped thousands of SAS professionals achieve their career goals. A study performed in 2016 by MONEY and Payscale examined the impact of skillsets on salary and found SAS to be the number one differentiator in pay with a 17% increase. Trained SAS users can discover, anticipate and capitalize on data-driven opportunities. These skills are in high demand in this big data world — it has never been a better time to learn SAS.

In this module you’ll learn how to: Apply data management techniques to prepare data for analysis and reporting. Visually explore data using SAS Visual Analytics Explorer, and perform analysis of variance, regression and logistic regression using SAS technology.

The courses in this module prepare you to take the first of two exams that are required to earn the SAS Certified Big Data Professional Using SAS 9 credential. As you study, be sure to take advantage of all the features of the Academy! Access all the SAS software you need for these courses by using the Virtual Lab Reservation System. Join the SAS Academy for Data Science online community to ask questions and share tips with your peers. SAS Certification practice exams are available through Pearson Vue. Information on how to purchase these exams is in the Virtual Learning Environment. You’ve made a smart choice for your future —┬ábest of luck on this part of your journey to becoming a SAS Certified Big Data Professional!

Course Curriculum

Welcome and Resources
Welcome and Resources 00:00:00
Tips for Using this Module
Tips for Using this Module 00:00:00
Preparing for Certification Exams
Preparing for Certification Exams 00:00:00

Course Reviews

N.A

ratings
  • 5 stars0
  • 4 stars0
  • 3 stars0
  • 2 stars0
  • 1 stars0

No Reviews found for this course.

PRIVATE COURSE
  • PRIVATE
  • 1 week, 3 days
0 STUDENTS ENROLLED
    Copyright @2019