Data Science for Business and Decision Making

Data Science for Business and Decision Making
Author: Luiz Paulo Fávero,Patrícia Belfiore
Publsiher: Academic Press
Total Pages: 1240
Release: 2019-04-11
ISBN 10: 0128112174
ISBN 13: 9780128112175
Language: EN, FR, DE, ES & NL

Data Science for Business and Decision Making Book Review:

Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work. Its emphasis reflects the importance of regression, optimization and simulation for practitioners of business analytics. Each chapter uses a didactic format that is followed by exercises and answers. Freely-accessible datasets enable students and professionals to work with Excel, Stata Statistical Software®, and IBM SPSS Statistics Software®. Combines statistics and operations research modeling to teach the principles of business analytics Written for students who want to apply statistics, optimization and multivariate modeling to gain competitive advantages in business Shows how powerful software packages, such as SPSS and Stata, can create graphical and numerical outputs

Data Science for Business and Decision Making

Data Science for Business and Decision Making
Author: Luiz Paulo Fávero,Patrícia Belfiore
Publsiher: Academic Press
Total Pages: 1000
Release: 2019-03-08
ISBN 10: 9780128112168
ISBN 13: 0128112166
Language: EN, FR, DE, ES & NL

Data Science for Business and Decision Making Book Review:

Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work. Its emphasis reflects the importance of regression, optimization and simulation for practitioners of business analytics. Each chapter uses a didactic format that is followed by exercises and answers. Freely-accessible datasets enable students and professionals to work with Excel, Stata Statistical Software®, and IBM SPSS Statistics Software®. Combines statistics and operations research modeling to teach the principles of business analytics Written for students who want to apply statistics, optimization and multivariate modeling to gain competitive advantages in business Shows how powerful software packages, such as SPSS and Stata, can create graphical and numerical outputs

Data Science for Business

Data Science for Business
Author: Foster Provost,Tom Fawcett
Publsiher: "O'Reilly Media, Inc."
Total Pages: 414
Release: 2013-07-27
ISBN 10: 144937428X
ISBN 13: 9781449374280
Language: EN, FR, DE, ES & NL

Data Science for Business Book Review:

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the "data-analytic thinking" necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today. Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides examples of real-world business problems to illustrate these principles. You’ll not only learn how to improve communication between business stakeholders and data scientists, but also how participate intelligently in your company’s data science projects. You’ll also discover how to think data-analytically, and fully appreciate how data science methods can support business decision-making. Understand how data science fits in your organization—and how you can use it for competitive advantage Treat data as a business asset that requires careful investment if you’re to gain real value Approach business problems data-analytically, using the data-mining process to gather good data in the most appropriate way Learn general concepts for actually extracting knowledge from data Apply data science principles when interviewing data science job candidates

Business Analytics for Decision Making

Business Analytics for Decision Making
Author: Steven Orla Kimbrough,Hoong Chuin Lau
Publsiher: CRC Press
Total Pages: 330
Release: 2016-07-31
ISBN 10: 1315360241
ISBN 13: 9781315360249
Language: EN, FR, DE, ES & NL

Business Analytics for Decision Making Book Review:

Business Analytics for Decision Making, the first complete text suitable for use in introductory Business Analytics courses, establishes a national syllabus for an emerging first course at an MBA or upper undergraduate level. This timely text is mainly about model analytics, particularly analytics for constrained optimization. It uses implementations that allow students to explore models and data for the sake of discovery, understanding, and decision making. Business analytics is about using data and models to solve various kinds of decision problems. There are three aspects for those who want to make the most of their analytics: encoding, solution design, and post-solution analysis. This textbook addresses all three. Emphasizing the use of constrained optimization models for decision making, the book concentrates on post-solution analysis of models. The text focuses on computationally challenging problems that commonly arise in business environments. Unique among business analytics texts, it emphasizes using heuristics for solving difficult optimization problems important in business practice by making best use of methods from Computer Science and Operations Research. Furthermore, case studies and examples illustrate the real-world applications of these methods. The authors supply examples in Excel®, GAMS, MATLAB®, and OPL. The metaheuristics code is also made available at the book's website in a documented library of Python modules, along with data and material for homework exercises. From the beginning, the authors emphasize analytics and de-emphasize representation and encoding so students will have plenty to sink their teeth into regardless of their computer programming experience.

Exam Prep for Data Science for Business and Decision Making

Exam Prep for  Data Science for Business and Decision Making
Author: Anonim
Publsiher: Unknown
Total Pages: 329
Release: 2021
ISBN 10:
ISBN 13:
Language: EN, FR, DE, ES & NL

Exam Prep for Data Science for Business and Decision Making Book Review:

Data Science for Business and Decision Making an Introductory Text for Students and Practitioners

Data Science for Business and Decision Making  an Introductory Text for Students and Practitioners
Author: Seyed Ali Fallahchay
Publsiher: Arcler Press
Total Pages: 329
Release: 2020-11
ISBN 10: 9781774076217
ISBN 13: 1774076217
Language: EN, FR, DE, ES & NL

Data Science for Business and Decision Making an Introductory Text for Students and Practitioners Book Review:

This book explores the principles underpinning data science. It considers the how and why of modern data science. The book goes further than existing books by applying data to decision making. Not only is the book useful for undergraduates, but it can also help business owners in improving their decision making. Using real life examples, this book explores the possibilities and limitations of an information-based decision making framework.

Getting Started with Business Analytics

Getting Started with Business Analytics
Author: David Roi Hardoon,Galit Shmueli
Publsiher: CRC Press
Total Pages: 190
Release: 2013-03-26
ISBN 10: 1439896534
ISBN 13: 9781439896532
Language: EN, FR, DE, ES & NL

Getting Started with Business Analytics Book Review:

Assuming no prior knowledge or technical skills, Getting Started with Business Analytics: Insightful Decision-Making explores the contents, capabilities, and applications of business analytics. It bridges the worlds of business and statistics and describes business analytics from a non-commercial standpoint. The authors demystify the main concepts and terminologies and give many examples of real-world applications. The first part of the book introduces business data and recent technologies that have promoted fact-based decision-making. The authors look at how business intelligence differs from business analytics. They also discuss the main components of a business analytics application and the various requirements for integrating business with analytics. The second part presents the technologies underlying business analytics: data mining and data analytics. The book helps you understand the key concepts and ideas behind data mining and shows how data mining has expanded into data analytics when considering new types of data such as network and text data. The third part explores business analytics in depth, covering customer, social, and operational analytics. Each chapter in this part incorporates hands-on projects based on publicly available data. Helping you make sound decisions based on hard data, this self-contained guide provides an integrated framework for data mining in business analytics. It takes you on a journey through this data-rich world, showing you how to deploy business analytics solutions in your organization.

Management Decision Making Big Data and Analytics

Management Decision Making  Big Data and Analytics
Author: Simone Gressel,David J. Pauleen,Nazim Taskin
Publsiher: SAGE
Total Pages: 336
Release: 2020-10-12
ISBN 10: 1529738288
ISBN 13: 9781529738285
Language: EN, FR, DE, ES & NL

Management Decision Making Big Data and Analytics Book Review:

Accessible and concise, this exciting new textbook examines data analytics from a managerial and organizational perspective and looks at how they can help managers become more effective decision-makers. The book successfully combines theory with practical application, featuring case studies, examples and a ‘critical incidents’ feature that make these topics engaging and relevant for students of business and management. The book features chapters on cutting-edge topics, including: • Big data • Analytics • Managing emerging technologies and decision-making • Managing the ethics, security, privacy and legal aspects of data-driven decision-making The book is accompanied by an Instructor’s Manual, PowerPoint slides and access to journal articles. Suitable for management students studying business analytics and decision-making at undergraduate, postgraduate and MBA levels.

Exam Prep Flash Cards for Data Science for Business and

Exam Prep Flash Cards for Data Science for Business and
Author: Anonim
Publsiher: Unknown
Total Pages: 329
Release: 2021
ISBN 10:
ISBN 13:
Language: EN, FR, DE, ES & NL

Exam Prep Flash Cards for Data Science for Business and Book Review:

Customer and Business Analytics

Customer and Business Analytics
Author: Daniel S. Putler,Robert E. Krider
Publsiher: CRC Press
Total Pages: 315
Release: 2015-09-15
ISBN 10: 149875970X
ISBN 13: 9781498759700
Language: EN, FR, DE, ES & NL

Customer and Business Analytics Book Review:

Customer and Business Analytics: Applied Data Mining for Business Decision Making Using R explains and demonstrates, via the accompanying open-source software, how advanced analytical tools can address various business problems. It also gives insight into some of the challenges faced when deploying these tools. Extensively classroom-tested, the text is ideal for students in customer and business analytics or applied data mining as well as professionals in small- to medium-sized organizations. The book offers an intuitive understanding of how different analytics algorithms work. Where necessary, the authors explain the underlying mathematics in an accessible manner. Each technique presented includes a detailed tutorial that enables hands-on experience with real data. The authors also discuss issues often encountered in applied data mining projects and present the CRISP-DM process model as a practical framework for organizing these projects. Showing how data mining can improve the performance of organizations, this book and its R-based software provide the skills and tools needed to successfully develop advanced analytics capabilities.

The Decision Maker s Handbook to Data Science

The Decision Maker s Handbook to Data Science
Author: Stylianos Kampakis
Publsiher: Apress
Total Pages: 156
Release: 2019-11-26
ISBN 10: 1484254945
ISBN 13: 9781484254943
Language: EN, FR, DE, ES & NL

The Decision Maker s Handbook to Data Science Book Review:

Data science is expanding across industries at a rapid pace, and the companies first to adopt best practices will gain a significant advantage. To reap the benefits, decision makers need to have a confident understanding of data science and its application in their organization. It is easy for novices to the subject to feel paralyzed by intimidating buzzwords, but what many don’t realize is that data science is in fact quite multidisciplinary—useful in the hands of business analysts, communications strategists, designers, and more. With the second edition of The Decision Maker’s Handbook to Data Science, you will learn how to think like a veteran data scientist and approach solutions to business problems in an entirely new way. Author Stylianos Kampakis provides you with the expertise and tools required to develop a solid data strategy that is continuously effective. Ethics and legal issues surrounding data collection and algorithmic bias are some common pitfalls that Kampakis helps you avoid, while guiding you on the path to build a thriving data science culture at your organization. This updated and revised second edition, includes plenty of case studies, tools for project assessment, and expanded content for hiring and managing data scientists Data science is a language that everyone at a modern company should understand across departments. Friction in communication arises most often when management does not connect with what a data scientist is doing or how impactful data collection and storage can be for their organization. The Decision Maker’s Handbook to Data Science bridges this gap and readies you for both the present and future of your workplace in this engaging, comprehensive guide. What You Will Learn Understand how data science can be used within your business. Recognize the differences between AI, machine learning, and statistics. Become skilled at thinking like a data scientist, without being one. Discover how to hire and manage data scientists. Comprehend how to build the right environment in order to make your organization data-driven. Who This Book Is For Startup founders, product managers, higher level managers, and any other non-technical decision makers who are thinking to implement data science in their organization and hire data scientists. A secondary audience includes people looking for a soft introduction into the subject of data science.

Business Analytics Data Analysis Decision Making

Business Analytics  Data Analysis   Decision Making
Author: S. Christian Albright,Wayne L. Winston
Publsiher: Cengage Learning
Total Pages: 984
Release: 2016-03-31
ISBN 10: 1337225274
ISBN 13: 9781337225274
Language: EN, FR, DE, ES & NL

Business Analytics Data Analysis Decision Making Book Review:

Master data analysis, modeling, and spreadsheet use with BUSINESS ANALYTICS: DATA ANALYSIS AND DECISION MAKING, 6E! Popular with students, instructors, and practitioners, this quantitative methods text delivers the tools to succeed with its proven teach-by-example approach, user-friendly writing style, and complete Excel 2016 integration. It is also compatible with Excel 2013, 2010, and 2007. Completely rewritten, Chapter 17, Data Mining, and Chapter 18, Importing Data into Excel, include increased emphasis on the tools commonly included under the Business Analytics umbrella -- including Microsoft Excel’s “Power BI” suite. In addition, up-to-date problem sets and cases provide realistic examples to show the relevance of the material. Important Notice: Media content referenced within the product description or the product text may not be available in the ebook version.

Business Intelligence

Business Intelligence
Author: Carlo Vercellis
Publsiher: John Wiley & Sons
Total Pages: 436
Release: 2011-08-10
ISBN 10: 1119965470
ISBN 13: 9781119965473
Language: EN, FR, DE, ES & NL

Business Intelligence Book Review:

Business intelligence is a broad category of applications and technologies for gathering, providing access to, and analyzing data for the purpose of helping enterprise users make better business decisions. The term implies having a comprehensive knowledge of all factors that affect a business, such as customers, competitors, business partners, economic environment, and internal operations, therefore enabling optimal decisions to be made. Business Intelligence provides readers with an introduction and practical guide to the mathematical models and analysis methodologies vital to business intelligence. This book: Combines detailed coverage with a practical guide to the mathematical models and analysis methodologies of business intelligence. Covers all the hot topics such as data warehousing, data mining and its applications, machine learning, classification, supply optimization models, decision support systems, and analytical methods for performance evaluation. Is made accessible to readers through the careful definition and introduction of each concept, followed by the extensive use of examples and numerous real-life case studies. Explains how to utilise mathematical models and analysis models to make effective and good quality business decisions. This book is aimed at postgraduate students following data analysis and data mining courses. Researchers looking for a systematic and broad coverage of topics in operations research and mathematical models for decision-making will find this an invaluable guide.

A PRACTITIONER S GUIDE TO BUSINESS ANALYTICS Using Data Analysis Tools to Improve Your Organization s Decision Making and Strategy

A PRACTITIONER S GUIDE TO BUSINESS ANALYTICS  Using Data Analysis Tools to Improve Your Organization   s Decision Making and Strategy
Author: Randy Bartlett
Publsiher: McGraw Hill Professional
Total Pages: 256
Release: 2013-01-25
ISBN 10: 0071807608
ISBN 13: 9780071807609
Language: EN, FR, DE, ES & NL

A PRACTITIONER S GUIDE TO BUSINESS ANALYTICS Using Data Analysis Tools to Improve Your Organization s Decision Making and Strategy Book Review:

Gain the competitive edge with the smart use of business analytics In today’s volatile business environment, the strategic use of business analytics is more important than ever. A Practitioners Guide to Business Analytics helps you get the organizational commitment you need to get business analytics up and running in your company. It provides solutions for meeting the strategic challenges of applying analytics, such as: Integrating analytics into decision making, corporate culture, and business strategy Leading and organizing analytics within the corporation Applying statistical qualifications, statistical diagnostics, and statistical review Providing effective building blocks to support analytics—statistical software, data collection, and data management Randy Bartlett, Ph.D., is Chief Statistical Officer of the consulting company Blue Sigma Analytics. He currently works with Infosys, where he has helped build their new Business Analytics practice.

Evidence Based Decision Making

Evidence Based Decision Making
Author: Andrew D. Banasiewicz
Publsiher: Routledge
Total Pages: 270
Release: 2019-03-04
ISBN 10: 1351050060
ISBN 13: 9781351050067
Language: EN, FR, DE, ES & NL

Evidence Based Decision Making Book Review:

Evidence-Based Decision-Making: How to Leverage Available Data and Avoid Cognitive Biases examines how a wide range of factual evidence, primarily derived from a variety of data available to organizations, can be used to improve the quality of business decision-making, by helping decision makers circumvent the various cognitive biases that adversely impact how we all think. The book is built on the following premise: During the past decade, the new ‘data world’ emerged, in which the rush to develop competencies around business analytics and data science can be characterized as nothing less than the new commercial arms race. The ever-expanding volume and variety of data are well known, as are the great advances in data processing/analytics, data visualization, and related information production-focused capabilities. Yet, comparatively little effort has been devoted to how the informational products of business analytics and data science are ‘consumed’ or used in the organizational decision-making processes, as the available evidence shows that only some of that information is used to drive some business decisions some of the time. Evidence-Based Decision-Making details an explicit process describing how the universe of available and applicable evidence, which includes organizational and other data, industry benchmarks, scientific studies, and professional experience, can be assessed, amalgamated, and funneled into an objective driver of key business decisions. Introducing key concepts in relation to data and evidence, and the history of evidence-based management, this new and extremely topical book will be essential reading for researchers and students of data analytics as well as those working in the private and public sectors, and in the voluntary sector.

Big Data Mining and Analytics

Big Data  Mining  and Analytics
Author: Stephan Kudyba
Publsiher: CRC Press
Total Pages: 325
Release: 2014-03-12
ISBN 10: 1466568712
ISBN 13: 9781466568716
Language: EN, FR, DE, ES & NL

Big Data Mining and Analytics Book Review:

There is an ongoing data explosion transpiring that will make previous creations, collections, and storage of data look trivial. Big Data, Mining, and Analytics: Components of Strategic Decision Making ties together big data, data mining, and analytics to explain how readers can leverage them to extract valuable insights from their data. Facilitati

Big Data Analytics Using Multiple Criteria Decision Making Models

Big Data Analytics Using Multiple Criteria Decision Making Models
Author: Ramakrishnan Ramanathan,Muthu Mathirajan,A. Ravi Ravindran
Publsiher: CRC Press
Total Pages: 370
Release: 2017-07-12
ISBN 10: 1351648691
ISBN 13: 9781351648691
Language: EN, FR, DE, ES & NL

Big Data Analytics Using Multiple Criteria Decision Making Models Book Review:

Multiple Criteria Decision Making (MCDM) is a subfield of Operations Research, dealing with decision making problems. A decision-making problem is characterized by the need to choose one or a few among a number of alternatives. The field of MCDM assumes special importance in this era of Big Data and Business Analytics. In this volume, the focus will be on modelling-based tools for Business Analytics (BA), with exclusive focus on the sub-field of MCDM within the domain of operations research. The book will include an Introduction to Big Data and Business Analytics, and challenges and opportunities for developing MCDM models in the era of Big Data.

Wisdom Analytics and Wicked Problems

Wisdom  Analytics and Wicked Problems
Author: Ali Intezari,David Pauleen
Publsiher: Taylor & Francis
Total Pages: 202
Release: 2018-11-02
ISBN 10: 1134769679
ISBN 13: 9781134769674
Language: EN, FR, DE, ES & NL

Wisdom Analytics and Wicked Problems Book Review:

The challenges faced by 21st-century businesses, organizations and governments are characterized as being fundamentally different in nature, scope and levels of impact from those of the past. As problems become increasingly complex and wicked, conventional reductive approaches and data-based solutions are limited. The authors argue that practical wisdom is required. This book provides an integral and practical model for incorporating wisdom into management decision making. Based on a cross-disciplinary conceptualization of practical wisdom, the authors distinguish systematically between data, information, knowledge, and wisdom-based decision making. While they suggest that data, analytics, information and knowledge can assist decision-makers to better deal with complex and wicked problems, they argue that data-based systems cannot replace optimized human decision-making capabilities. These capabilities, the authors explain, include a range of qualities and characteristics inherent in philosophical, psychological and organizational conceptions of practical wisdom. Accordingly, in this book, the authors introduce a model that identifies the specific qualities and processes involved in making wise decisions, especially in management. The model is based on the empirical fi ndings of the authors’ studies in the areas of wisdom and management. This book is a practical resource for professionals, practitioners, and consultants in both the private and public sectors. The theoretical discussions, critical arguments, and practical guidelines provided in the book will be extremely valuable to students at the undergraduate and postgraduate levels, as well as upper-level postdoctoral researchers looking at business management strategies.

Behind Every Good Decision

Behind Every Good Decision
Author: Piyanka Jain,Puneet Sharma
Publsiher: AMACOM
Total Pages: 256
Release: 2014-11-05
ISBN 10: 0814449220
ISBN 13: 9780814449226
Language: EN, FR, DE, ES & NL

Behind Every Good Decision Book Review:

So you’re not a numbers person? No worries! You say that you can’t understand how to read, let alone implement, these complex software programs that crunch all the data and spit out . . . more data? Not a problem either! There is a costly misconception in business today--that the only data that matters is BIG data, and that elaborate tools and data scientists are required to extract any practical information. But actually, nothing could be further from the truth.In Behind Every Good Decision, authors and analytics experts Piyanka Jain and Puneet Sharma demystify the process of business analytics and demonstrate how professionals at any level can take the information at their disposal and in only five simple steps--using only Excel as a tool!--make the decision necessary to increase revenue, decrease costs, improve product, or whatever else is being asked of them at that time. Readers will learn how to:• Clarify the business question• Lay out a hypothesis-driven plan• Pull relevant data• Convert it to insights• Make decisions that make an impactPacked with examples and exercises, this refreshingly accessible book explains the four fundamental analytic techniques that can help solve a surprising 80 percent of all business problems. It doesn’t take a numbers person to know that is a formula you need!

Real World Data Mining

Real World Data Mining
Author: Dursun Delen
Publsiher: FT Press
Total Pages: 288
Release: 2014-12-16
ISBN 10: 0133551113
ISBN 13: 9780133551112
Language: EN, FR, DE, ES & NL

Real World Data Mining Book Review:

Use the latest data mining best practices to enable timely, actionable, evidence-based decision making throughout your organization! Real-World Data Mining demystifies current best practices, showing how to use data mining to uncover hidden patterns and correlations, and leverage these to improve all aspects of business performance. Drawing on extensive experience as a researcher, practitioner, and instructor, Dr. Dursun Delen delivers an optimal balance of concepts, techniques and applications. Without compromising either simplicity or clarity, he provides enough technical depth to help readers truly understand how data mining technologies work. Coverage includes: processes, methods, techniques, tools, and metrics; the role and management of data; text and web mining; sentiment analysis; and Big Data integration. Throughout, Delen's conceptual coverage is complemented with application case studies (examples of both successes and failures), as well as simple, hands-on tutorials. Real-World Data Mining will be valuable to professionals on analytics teams; professionals seeking certification in the field; and undergraduate or graduate students in any analytics program: concentrations, certificate-based, or degree-based.