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- 1. edureka! BusinessAnalytics With R
- 2. Business Analytics and Data Science
- 3. How it works? • 6 weeks duration • 2 hour live online sessions every Saturday and Sunday • • • • • • Total 8 hours per week = 4 hours (in class) + 4 hours (assignments and case studies) Project Work (~15 hours) 2 hour proctored Final Online Exam* All classes are recorded and recordings will be shared even in downloadable format All course material (ppt,pdfs,assignments,etc) will be shared as soft copy Life time access to the Learning Management System (LMS)** *Problem based exam **24 X 7 Online Support
- 4. Course Topics Class 1 Introduction to Business Analytics Introduction to Data Science Introduction to R Class 2 Class 3 Class 4 Class 5 Class 6 Data Import in R Introduction to Business Analytics Data Quality in R Data Manipulation in R Exploratory Data Analysis in R Data Visualization in R Class 7 Data Mining in R (P1) Class 8 Data Mining in R (P2) Class 9 Understanding Model Building in R (P1) Class 10 Understanding Model Building in R (P2) Class 11 Advanced Topics in R Class 12 Revision and Final Exam
- 5. Introduction Learning Objectives By the end of this chapter, • Know more on business analytics , data science and R • Know more on the R language, community and ecosystem • Understand how 'R' is being used in the industry • Compare R with other software in analytics • Install R and packages which are going to be used for the course • Do basic operations in R using command line • Learn how to use the IDE R Studio and Various GUI • Use the R help • Be introduced to how the worldwide R community collaborates
- 6. Business Analytics Definition “Study of business data using statistical techniques and programming for creating decision support and insights for achieving business goals” Who uses it? How? • Across Domain • Dashboard • Models • Across A Company Who creates it? How? • Skills Needed Business Perception
- 7. Business Intelligence
- 8. What Is Data Science? Conway's Diagram https://s3.amazonaws.com/aws.drewconway.com/viz/venn_diagram/data_science.html
- 9. Studying Data Science? • Coursera Courses ( 26 Courses at https://www.coursera.org/courses?orderby=upcoming&cats=stats • Computational Methods for Data Analysis https://www.coursera.org/course/compmethods • Computing for Data Analysis https://www.coursera.org/course/compdata • Introduction to Data Science https://www.coursera.org/course/datasci • Machine Learning https://www.coursera.org/course/ml
- 10. Course Design Business Analytics • Understanding what solution business needs Data Science • Primarily R • Programming skills • Some Applied Statistical Methods • Exposure to new domains and techniques
- 11. Course Design What you will learn ? • Data Visualization • Data Mining Techniques • Clustering • Association Analysis • Modeling(including Regression) • What is Demand Forecasting • Data Manipulation
- 12. Course Design What you may learn a bit? • Infographics • Business Strategy Models • Data Mining Techniques • SVM and Decision Trees • Neutral Nets and Ensemble Models • Web Analytics and Social Media Analytics • Social Network Analysis(SNA)
- 13. Course Design • What you may NOT learn?
- 14. Course Methodology
- 15. Part 1: What Is Business Analytics? • What are the problems in a business ? • What are the tools that can be used? • How are businesses solving these problems? • What problems can be solved by MS Excel? • What can’t be solved by MS Excel?
- 16. Part 1: What Is Business Analytics? • What is Business Analytics • What problems does it solve? • History of Business Analytics. • What are the different kinds of Business Analytics? • What is R? What is SAS? • How are they different?
- 17. Part 1: What Is Business Analytics?
- 18. • Part 1 - What is R? • Part 2 - Corporate usage for R • Part 3 - Comparing R • Part 4 - Installation of R and Packages • Part 5 - Basics of R - Command Line • Part 6 - RStudio IDE and GUI • Part 7 - Help and Documentation in R • Part 8 - Interacting with community in R Topics: Introduction To R
- 19. Part 1: What Is R? www.r-project.org/
- 20. Part 1: What Is R? www.r-project.org/about.html History Open Source Official Website R Journal Evolution Free R Core Current State Widely Recognized Creators
- 21. Part 2: Corporate Usage of R?
- 22. Part 2: Corporate Usage of R?
- 23. Part 2: Corporate Usage of R? Did you know Oracle creates a version of R? http://www.oracle.com/technetwork/topics/bigdata/r-offerings-1566363.html
- 24. Part 2: Corporate Usage of R? Did you know SAP uses R for analyzing it’s HANA database? http://help.sap.com/hana/hana_dev_r_emb_en.pdf
- 25. Part 2: Corporate Usage of R? Did you know SAS Institute views R as an Opportunity? http://support.sas.com/rnd/app/studio/Rinterface2.html
- 26. Part 2: Corporate Usage of R? Did you know SAS Institute views R as an Opportunity? http://support.sas.com/rnd/app/studio/Rinterface2.html
- 27. Part 2: Corporate Usage of R? Did you know SAS Institute views R as an Opportunity? http://www.jmp.com/support/help/Working_with_R.shtml
- 28. Part 2: Corporate Usage of R? Did you know Teradata uses R for in-database analytics? http://developer.teradata.com/applications/articles/in-database-analytics-with-teradata-r http://downloads.teradata.com/download/applications/teradata-r
- 29. Part 2: Corporate Usage of R? Did you know IBM uses and even teaches R for High-end Analytics? http://www-304.ibm.com/jct03001c/services/learning/ites.wss/us/en?pageType=course_description&courseCode=DW540
- 30. Part 2: Corporate Usage of R? • Telecom • Pharmaceuticals • Financial Services • Life sciences, etc
- 31. Corporate Clients of R http://www.revolutionanalytics.com/aboutus/our-customers.php Part 2: Corporate Usage of R?
- 32. Part 3: Comparing R
- 33. but R is open source and free R has a steep learning curve Part 3: Comparing R R has lots of packages R can be customized R has the most advanced graphics R has GUI to help make learning easier R can connect to many database and data types multiple packages and ways to do the same thing by default stores memory in RAM you need much better programming skills customization needs command line you need to know which package to use
- 34. Comparing R and Base SAS* /SAS Stat* R is open source and free Base SAS* , SAS/Stat*, SAS/ET*, SAS/OR*, SAS/Graph* are expensive relatively because of annual licenses SAS Institute* products have dedicated support and extensive documentation by default R stores memory in RAM,so we can use the cloud you need much better programming skills Part 3: Comparing R Open source R has support from email lists, twitter, stack overflow R is slower on the desktop than base SAS for datasets ~4-5 gb R has much much better graphics You can create custom functions in R easily R has multiple GUI that are free *Copyright © 2012 SAS Institute Inc., SAS Campus Drive, Cary, North Carolina 27513, USA. All rights reserved. Customization needs command line SAS GUI are more expensive but
- 35. Comparing R and others http://r4stats.com/articles/popularity/ Part 3: Comparing R
- 36. http://cran.r-project.org/ http://cran.r-project.org/bin/windows/Rtools/ Part 4: Installation of R and Packages
- 37. Part 4: Installation of R and Packages http://cran.r-project.org/
- 38. Part 4: Installation of R and Packages http://cran.r-project.org/ http://cran.r-project.org/bin/windows/Rtools/
- 39. Part 4: Installation of R and Packages http://cran.r-project.org/ http://cran.r-project.org/bin/windows/Rtools/
- 40. R and R Packages Part 4: Installation of R and Packages
- 41. Part 4: Installation of R and Packages R and R Packages
- 42. Part 4: Installation of R and Packages R and R Packages
- 43. Part 4: Installation of R and Packages R and R Packages
- 44. Part 4: Installation of R and Packages R and R Packages
- 45. Part 5: Basics Of R - Command Line Basics of R - Command Line
- 46. Part 5: Basics Of R - Command Line Basics of R - Command Line
- 47. Basics of R - Command Line Part 5: Basics Of R - Command Line
- 48. Part 6: RStudio IDE and GUI Installation of RStudio
- 49. Thank You See You in Class Next Week

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