Practical Business Analytics Using SAS: A Hands-on Guide / Edition 1

Practical Business Analytics Using SAS: A Hands-on Guide / Edition 1

ISBN-10:
1484200446
ISBN-13:
9781484200445
Pub. Date:
01/30/2015
Publisher:
Apress
ISBN-10:
1484200446
ISBN-13:
9781484200445
Pub. Date:
01/30/2015
Publisher:
Apress
Practical Business Analytics Using SAS: A Hands-on Guide / Edition 1

Practical Business Analytics Using SAS: A Hands-on Guide / Edition 1

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Overview

Practical Business Analytics Using SAS: A Hands-on Guide shows SAS users and businesspeople how to analyze data effectively in real-life business scenarios.

The book begins with an introduction to analytics, analytical tools, and SAS programming. The authors—both SAS, statistics, analytics, and big data experts—first show how SAS is used in business, and then how to get started programming in SAS by importing data and learning how to manipulate it. Besides illustrating SAS basic functions, you will see how each function can be used to get the information you need to improve business performance. Each chapter offers hands-on exercises drawn from real business situations.

The book then provides an overview of statistics, as well as instruction on exploring data, preparing it for analysis, and testing hypotheses. You will learn how to use SAS to perform analytics and model using both basic and advanced techniques like multiple regression, logistic regression, and time series analysis, among other topics. The book concludes with a chapter on analyzing big data. Illustrations from banking and other industries make the principles and methods come to life.

Readers will find just enough theory to understand the practical examples and case studies, which cover all industries. Written for a corporate IT and programming audience that wants to upgrade skills or enter the analytics field, this book includes:



• More than 200 examples and exercises, including code and datasets for practice.
• Relevant examples for all industries.
• Case studies that show how to use SAS analytics to identify opportunities, solve complicated problems, and chart a course.

Practical Business Analytics Using SAS: A Hands-on Guide gives you the tools you need to gain insight into the data at your fingertips, predict business conditions for better planning, and make excellent decisions. Whether you are in retail, finance, healthcare, manufacturing, government, or any other industry, this book will help your organization increase revenue, drive down costs, improve marketing, and satisfy customers better than ever before.


Product Details

ISBN-13: 9781484200445
Publisher: Apress
Publication date: 01/30/2015
Edition description: 1st ed.
Pages: 580
Product dimensions: 7.01(w) x 10.00(h) x (d)

About the Author

Shailendra Kadre is a senior IT and management consultant from Bangalore, India. He is the author of a 2011 Apress book, Going Corporate: A Geek’s Guide, which covers IT operations management and the business aspects of IT. He has more than 20 years of experience in manufacturing, IT delivery and operations, program management, pre-sales, enterprise sales, and business analytics. Currently, he is working with Hewlett-Packard India as a solutions consultant. His current interests include business analytics and enterprise printing solutions.Shailendra earned his master’s degree in mechanical engineering from the Indian Institute of Technology (IIT), Delhi. He lives in Bangalore with his wife Meenakshi, daughter Neha, and son Vivek. He can be contacted at shailendrakadre@gmail.com.

Table of Contents

Part One: Basics of SAS Programming for Analytics

Chapter 01 Introduction to Business Analytics and Data Analysis Tools

Chapter 02: SAS Introduction

Chapter 03: SAS Handling Using SAS

Chapter 04 : Important SAS Functions and Procs

Part Two: Using SAS for Business Analytics

Chapter 05 Introduction to Statistical Analysis

Chapter 06 Basic Descriptive Statistics

Chapter 07 Data Exploration, Validation, and Data Sanitization

Chapter 08 Testing of Hypothesis

Chapter 09 Correlation and Linear Regression

Chapter 10 Multiple Regression Analysis

Chapter 11: Logistic Regression

Chapter 12: Time Series Analysis and Forecasting

Chapter 13: Introducing Big Data Analytics

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