Analytics, Data Science, & Artificial Intelligence - Systems for Decision Support - 11th Edition

Sep 11, 2026

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Eleventh Edition presents integrated analytics, data science, and artificial intelligence systems designed to support decision-making across business contexts. The work guides readers from core concepts of business intelligence, AI drivers, data nature, statistical modeling, and visualization through predictive analytics and machine learning, including deep learning, cognitive computing, and text mining. It then extends to prescriptive analytics, big data, cloud and location analytics, and finally to robotics, social networks, knowledge systems, and IoT.

LanguageEnglish

CategoryTechnology

FormatPDF

Pages84

Reading Time3 h 32 min

AccessFree to download

Preface

About the Authors

Part I Introduction to Analytics and AI

Chapter 1 Overview of Business Intelligence, Analytics, Data Science, and Artificial Intelligence: Systems for Decision Support

Chapter 2 Artificial Intelligence: Concepts, Drivers, Major Technologies, and Business Applications

Chapter 3 Nature of Data, Statistical Modeling, and Visualization

Part II Predictive Analytics/Machine Learning

Chapter 4 Data Mining Process, Methods, and Algorithms

Chapter 5 Machine-Learning Techniques for Predictive Analytics

Chapter 6 Deep Learning and Cognitive Computing

Chapter 7 Text Mining, Sentiment Analysis, and Social Analytics

Part III Prescriptive Analytics and Big Data

Chapter 8 Prescriptive Analytics: Optimization and Simulation

Chapter 9 Big Data, Cloud Computing, and Location Analytics: Concepts and Tools

Part IV Robotics, Social Networks, AI and IoT

Chapter 10 Robotics: Industrial and Consumer Applications

Chapter 11 Group Decision Making, Collaborative Systems, and AI Support

Chapter 12 Knowledge Systems: Expert Systems, Recommenders, Chatbots, Virtual Personal Assistants, and Robo Advisors

Chapter 13 The Internet of Things

E L E V E N T H E D I T I O N G L O B A L E D I T I O N ANALYTICS, DATA SCIENCE, & ARTIFICIAL INTELLIGENCE SYSTEMS FOR DECISION SUPPORT Ramesh Sharda Oklahoma State University Dursun Delen Oklahoma State University Efraim Turban University of Hawaii Harlow, England • London • New York • Boston • San Francisco • Toronto • Sydney • Dubai • Singapore • Hong Kong Tokyo • Seoul • Taipei • New Delhi • Cape Town • Sao Paulo • Mexico City • Madrid • Amsterdam • Munich • Paris • Milan Please contact [https://support.pearson.com/getsupport/s/contactsupport with any queries](https://support.pearson.com/getsupport/s/contactsupport with any queries) on this content. Microsoft and/or its respective suppliers make no representations about the suitability of the information contained in the documents and related graphics published as part of the services for any purpose. All such documents and related graphics are provided “as is” without warranty of any kind. Microsoft and/or its respective suppliers hereby disclaim all warranties and conditions with regard to this information, including all warranties and conditions of merchantability, whether express, implied or statutory, fitness for a particular purpose, title and non-infringement. In no event shall Microsoft and/or its respective suppliers be liable for any special, indirect or consequential damages or any damages whatsoever resulting from loss of use, data or profits, whether in an action of contract, negligence or other tortious action, arising out of or in connection with the use or performance of information available from the services. The documents and related graphics contained herein could include technical inaccuracies or typographical errors. Changes are periodically added to the information herein. Microsoft and/or its respective suppliers may make improvements and/or changes in the product(s) and/or the program(s) described herein at any time. Partial screen shots may be viewed in full within the software version specified. Microsoft® and Windows® are registered trademarks of the Microsoft Corporation in the U.S.A. and other countries. This book is not sponsored or endorsed by or affiliated with the Microsoft Corporation Pearson Education Limited KAO Two KAO Park Hockham Way Harlow Essex CM17 9SR United Kingdom and Associated Companies throughout the world Visit us [on the World Wide Web at: www.pearsonglobaleditions.com](on the World Wide Web at: www.pearsonglobaleditions.com)[ ](on the World Wide Web at: www.pearsonglobaleditions.com)© Pearson Education Limited, 2021 The rights of Ramesh Sharda, Dursun Delen, and Efraim Turban to be identified as the authors of this work have been asserted by them in accordance with the Copyright, Designs and Patents Act 1988. Authorized adaptation from the United States edition, entitled Analytics, Data Science, & Artificial Intelligence: Systems for Decision Support, 11th Edition, ISBN 978-0-13-519201-6 by Ramesh Sharda, Dursun Delen, andEfraim Turban, published by Pearson Education © 2021. Acknowledgments of third-party content appear on the appropriate page within the text. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, recording or otherwise, without either the prior written permission of the publisher or a license permitting restricted copying in the United Kingdom issued by the Copyright Licensing Agency Ltd, Saffron House, 6–10 Kirby Street, London EC1N 8TS. PEARSON and ALWAYS LEARNING are exclusive trademarks owned by Pearson Education, Inc. or its affiliates in the U.S. and/ or other countries. All trademarks used herein are the property of their respective owners. The use of any trademark in this text does not vest in the author or publisher any trademark ownership rights in such trademarks, nor does the use of such trademarks imply any affiliatio

FAQs

What topics does this book cover across the decision-support pipeline?

It spans analytics foundations, predictive analytics and machine learning, prescriptive analytics and big data, and applications in robotics, social networks, knowledge systems, and IoT.

How does the book approach predictive analytics?

It focuses on data mining processes and methods, machine-learning techniques for predictive analytics, deep learning and cognitive computing, and text mining with sentiment and social analytics.

What are the prescriptive and big data components included?

Prescriptive analytics topics include optimization and simulation, along with big data, cloud computing, and location analytics concepts and tools.

Sep 11, 2026

Upload by Rhys