Data Science For Decision Makers

Author : Luiz Paulo Fávero,Patrícia Belfiore
Publisher : Academic Press
Page : 1240 pages
File Size : 55,8 Mb
Release : 2019-04-11
Category : Business & Economics
ISBN : 9780128112175

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Data Science for Business and Decision Making by Luiz Paulo Fávero,Patrícia Belfiore Pdf

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

Author : Stylianos Kampakis
Publisher : Apress
Page : 154 pages
File Size : 55,7 Mb
Release : 2019-11-26
Category : Computers
ISBN : 9781484254943

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The Decision Maker's Handbook to Data Science by Stylianos Kampakis Pdf

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.

Author : Gökhan Silahtaroğlu,Hasan Dinçer,Serhat Yüksel
Publisher : Springer Nature
Page : 183 pages
File Size : 43,5 Mb
Release : 2021-05-29
Category : Business & Economics
ISBN : 9783030741761

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Data Science and Multiple Criteria Decision Making Approaches in Finance by Gökhan Silahtaroğlu,Hasan Dinçer,Serhat Yüksel Pdf

This book considers and assesses essential financial issues by utilizing data science and fuzzy multiple criteria decision making (MCDM) methods. It introduces readers to a range of data science methods, and demonstrates their application in the fields of business, health, economics, finance and engineering. In addition, it provides suggestions based on the assessment results on each topic, which can help to enhance the efficiency of the financial system and the sustainability of economic development. Given its scope, the book will help readers broaden their perspective on the assessment and evaluation of financial issues using data science and MCDM approaches.

Author : Sergio Consoli,Diego Reforgiato Recupero,Michaela Saisana
Publisher : Springer Nature
Page : 357 pages
File Size : 54,9 Mb
Release : 2021
Category : Application software
ISBN : 9783030668914

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Data Science for Economics and Finance by Sergio Consoli,Diego Reforgiato Recupero,Michaela Saisana Pdf

This open access book covers the use of data science, including advanced machine learning, big data analytics, Semantic Web technologies, natural language processing, social media analysis, time series analysis, among others, for applications in economics and finance. In addition, it shows some successful applications of advanced data science solutions used to extract new knowledge from data in order to improve economic forecasting models. The book starts with an introduction on the use of data science technologies in economics and finance and is followed by thirteen chapters showing success stories of the application of specific data science methodologies, touching on particular topics related to novel big data sources and technologies for economic analysis (e.g. social media and news); big data models leveraging on supervised/unsupervised (deep) machine learning; natural language processing to build economic and financial indicators; and forecasting and nowcasting of economic variables through time series analysis. This book is relevant to all stakeholders involved in digital and data-intensive research in economics and finance, helping them to understand the main opportunities and challenges, become familiar with the latest methodological findings, and learn how to use and evaluate the performances of novel tools and frameworks. It primarily targets data scientists and business analysts exploiting data science technologies, and it will also be a useful resource to research students in disciplines and courses related to these topics. Overall, readers will learn modern and effective data science solutions to create tangible innovations for economic and financial applications.

Author : Simone Gressel,David J. Pauleen,Nazim Taskin
Publisher : SAGE
Page : 354 pages
File Size : 54,8 Mb
Release : 2020-10-12
Category : Business & Economics
ISBN : 9781529738285

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Management Decision-Making, Big Data and Analytics by Simone Gressel,David J. Pauleen,Nazim Taskin Pdf

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.

Author : Stylianos Kampakis
Publisher : Unknown
Page : 156 pages
File Size : 42,8 Mb
Release : 2020
Category : Big data
ISBN : 1484254953

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The Decision Maker's Handbook to Data Science by Stylianos Kampakis Pdf

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.

Author : Karen L. Webber,Henry Y. Zheng
Publisher : Johns Hopkins University Press
Page : 337 pages
File Size : 40,9 Mb
Release : 2020-11-03
Category : Education
ISBN : 9781421439037

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Big Data on Campus by Karen L. Webber,Henry Y. Zheng Pdf

Webber, Henry Y. Zheng, Ying Zhou

Author : Andrew D. Banasiewicz
Publisher : Routledge
Page : 270 pages
File Size : 54,8 Mb
Release : 2019-03-04
Category : Business & Economics
ISBN : 9781351050067

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Evidence-Based Decision-Making by Andrew D. Banasiewicz Pdf

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.

Author : David Roi Hardoon,Galit Shmueli
Publisher : CRC Press
Page : 192 pages
File Size : 53,5 Mb
Release : 2013-03-26
Category : Business & Economics
ISBN : 9781439896532

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Getting Started with Business Analytics by David Roi Hardoon,Galit Shmueli Pdf

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.

Author : Singh, Amandeep
Publisher : IGI Global
Page : 310 pages
File Size : 46,9 Mb
Release : 2021-06-18
Category : Business & Economics
ISBN : 9781799872337

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Big Data Analytics for Improved Accuracy, Efficiency, and Decision Making in Digital Marketing by Singh, Amandeep Pdf

The availability of big data, low-cost commodity hardware, and new information management and analytic software have produced a unique moment in the history of data analysis. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue, and profitability especially in digital marketing. Data plays a huge role in understanding valuable insights about target demographics and customer preferences. From every interaction with technology, regardless of whether it is active or passive, we are creating new data that can describe us. If analyzed correctly, these data points can explain a lot about our behavior, personalities, and life events. Companies can leverage these insights for product improvements, business strategy, and marketing campaigns to cater to the target customers. Big Data Analytics for Improved Accuracy, Efficiency, and Decision Making in Digital Marketing aids understanding of big data in terms of digital marketing for meaningful analysis of information that can improve marketing efforts and strategies using the latest digital techniques. The chapters cover a wide array of essential marketing topics and techniques, including search engine marketing, consumer behavior, social media marketing, online advertising, and how they interact with big data. This book is essential for professionals and researchers working in the field of analytics, data, and digital marketing, along with marketers, advertisers, brand managers, social media specialists, managers, sales professionals, practitioners, researchers, academicians, and students looking for the latest information on how big data is being used in digital marketing strategies.

Author : Eric Van Der Steen
Publisher : Passionned Publishers
Page : 432 pages
File Size : 49,8 Mb
Release : 2021-03-15
Category : Electronic
ISBN : 9082809176

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Data Science for Decision Makers & Data Professionals by Eric Van Der Steen Pdf

Learn how to embed data science, Big Data and AI in your organization's decision-making process and make your organization more data-driven, profitable, and intelligent in 10 steps. Book description This book covers every aspect of the implementation of data science, from the algorithms that make your decisions more refined, effective and faster to the people, skills, culture, and mindset required to make it happen. How do you set the right KPIs and targets? How are the best data-driven organizations structured? Why do you need a data warehouse or data lake? How do you manage a data science project? This book tackles every question relevant to implementing data science. Many organizations start by collecting data without a goal, but that data science approach is doomed to fail. This book takes you through the process of implementing data science from the ground floor all the way to the top. It all starts with the question: what do we want to achieve? It covers all the subsequent steps on a macro and micro level, from the process of registering data, to processing it, to the organization's response. All the relevant data science techniques and technologies are discussed, from algorithms and AI to the right management strategies. Based on many practical case studies and best practices, this book reveals what works and what doesn't. Benefit from the author's many years of experience in making organizations more intelligent and data-driven as a consultant and an educator. What you will learn - The most important benefits of data science. - The essential aspects of decision making and the role of data science. - How to determine the right KPIs and use them to manage effectively. - How to turn data into knowledge and information. - How to make your organization more agile. - The many types of algorithms that can be used to make more effective decisions on every level. - How to manage data science projects - who and what do you need to effectively implement data science? - How to design a data science roadmap. - And much, much more. Who is this book for This book is for every manager or professional, and all those who want to learn how to embed the effective use of data science in every facet of the organization. This comprehensive management handbook is a must-read for (business) consultants, business managers, Chief Data Officers (CDOs), CIOs, and other executives, project managers, Data Science consultants, Data Scientists, AI consultants, (business) controllers, quality managers, and BI consultants.

Author : Jay Liebowitz
Publisher : Taylor & Francis
Page : 169 pages
File Size : 43,6 Mb
Release : 2019-07-19
Category : Business & Economics
ISBN : 9781000024197

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Developing Informed Intuition for Decision-Making by Jay Liebowitz Pdf

This book examines how to develop the main traits that are necessary to become an “informed intuitant”. Case studies and examples of successful “informed intuitants” are a major component of the book. “Intuitant” is someone who has the intuitive awareness to be successful. “Informed intuitant” indicates that the individual/decision maker not only applies his/her intuition but also verifies it through using data-driven approaches (such as data analytics). Some of this work resulted from research examining how well do executives trust their intuition.

Author : Foster Provost,Tom Fawcett
Publisher : "O'Reilly Media, Inc."
Page : 414 pages
File Size : 42,8 Mb
Release : 2013-07-27
Category : Computers
ISBN : 9781449374280

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Data Science for Business by Foster Provost,Tom Fawcett Pdf

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

Author : S. Christian Albright,Wayne L. Winston
Publisher : Unknown
Page : 952 pages
File Size : 41,5 Mb
Release : 2017
Category : Decision making
ISBN : 9814834394

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Business Analytics by S. Christian Albright,Wayne L. Winston Pdf

Author : Patanjali Kashyap
Publisher : Apress
Page : 381 pages
File Size : 48,9 Mb
Release : 2018-01-04
Category : Computers
ISBN : 9781484229880

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Machine Learning for Decision Makers by Patanjali Kashyap Pdf

Take a deep dive into the concepts of machine learning as they apply to contemporary business and management. You will learn how machine learning techniques are used to solve fundamental and complex problems in society and industry. Machine Learning for Decision Makers serves as an excellent resource for establishing the relationship of machine learning with IoT, big data, and cognitive and cloud computing to give you an overview of how these modern areas of computing relate to each other. This book introduces a collection of the most important concepts of machine learning and sets them in context with other vital technologies that decision makers need to know about. These concepts span the process from envisioning the problem to applying machine-learning techniques to your particular situation. This discussion also provides an insight to help deploy the results to improve decision-making. The book uses case studies and jargon busting to help you grasp the theory of machine learning quickly. You'll soon gain the big picture of machine learning and how it fits with other cutting-edge IT services. This knowledge will give you confidence in your decisions for the future of your business. What You Will Learn Discover the machine learning, big data, and cloud and cognitive computing technology stack Gain insights into machine learning concepts and practices Understand business and enterprise decision-making using machine learning Absorb machine-learning best practices Who This Book Is For Managers tasked with making key decisions who want to learn how and when machine learning and related technologies can help them.