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Apply analytics to business problems using two very popular software tools, SAS and R. No matter your industry, this book will provide you with the knowledge and insights you and your business partners need to make better decisions faster.

Learn Business Analytics in Six Steps Using SAS and R teaches you how to solve problems and execute projects through the "DCOVA and I" (Define, Collect, Organize, Visualize, Analyze, and Insights) process. You no longer need to choose between the two most popular software tools. This book puts the best of both worlds-SAS and R-at your fingertips to solve a myriad of problems, whether relating to data science, finance, web usage, product development, or any other business discipline.

What You´ll Learn

Use the DCOVA and I process: Define, Collect, Organize, Visualize, Analyze and Insights.
Harness both SAS and R, the star analytics technologies in the industry
Use various tools to solve significant business challenges
Understand how the tools relate to business analytics
See seven case studies for hands-on practice Who This Book Is For
This book is for all IT professionals, especially data analysts, as well as anyone who

Likes to solve business problems and is good with logical thinking and numbers
Wants to enter the analytics world and is looking for a structured book to reach that goal
Is currently working on SAS , R, or any other analytics software and strives to use its full power

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Chapter Description and Details

1 The Process of Analytics: DCOVA and I

1.1 What is analytics?

1.2 The process of Analytics

1.2.1 Define

1.2.2 Collect

1.2.3 Organize

1.2.4 Visualize

1.2.5 Analyze

1.2.6 Insight

2 Accessing SAS and R

2.1 Why SAS and R

2.2 History of SAS and R

2.3 Installing SAS and R

3 Data Manipulation using SAS and R: Collecting and Organizing the Data

3.1 Data flow from ERP to Business Analytics SaaS

3.2 Sanity check on data

3.3 Merging datasets

3.4 Missing values, Duplication , Outliers

3.5 Project datamart

4 Discover basic information about data

4.1 Descriptive statistics , measures of central tendency, measures of variation

4.2 How to generate them using:

4.2.1 SAS

4.2.2 R

5 Visualisation

5.1 Graphs and charts

5.2 How to create effective graphs and charts using:

5.2.1 SAS

5.2.2 R

5.3 Correlation and co-variance

5.4 How to create graphical and numeric outputs for correlation and co-variance using

5.4.1 SAS

5.4.2 R

6 Analyze: Probability and Distributions

6.1 Concepts of probability

6.2 How to generate probability using:

6.2.1 SAS

6.2.2 R

6.3 Concepts of distributions

6.4 Normal distributions

6.5 How to work on distributions using:

6.5.1 SAS

6.5.2 R

7 Analyze: Sampling and Sampling Distributions

7.1 Sampling and sampling distributions

7.2 Hypothesis testing

7.3 How to work on sampling and hypothesis testing using:

7.3.1 SAS
7.3.2 R

8 Analyze: Confidence Interval

8.1 Concept of confidence interval

8.2 How to work in confidence intervals using

8.2.1 SAS

8.2.2 R

9 Insight Generation

9.1 What type of conclusions can be drawn by the analysis

9.2 Interpreting results generated by:

9.2.1 SAS

9.2.2 R

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Subhashini Tripathi is an enthusiastic analytics professional focused on learning, training and development, and consulting projects, especially those related to analytics practice, in SBUs, SMEs , NGOs and start-ups. Subhashini is based out of Bangalore and is currently involved in consulting assignments with various corporations and educational institutions. She is a CompTIA Certified Technical Trainer.

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