Data Science For Decision Makers Data Professionals

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Data Science for Business and Decision Making

Luiz Paulo Fávero,Patrícia Belfiore
Data Science for Business and Decision Making Book PDF

Author : Luiz Paulo Fávero,Patrícia Belfiore
Publisher : Academic Press
Page : 1240 pages
File Size : 55,5 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

Data Science for Decision Makers & Data Professionals

Eric Van Der Steen
Data Science for Decision Makers Data Professionals Book PDF

Author : Eric Van Der Steen
Publisher : Passionned Publishers
Page : 432 pages
File Size : 55,5 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.

The Decision Maker's Handbook to Data Science

Stylianos Kampakis
The Decision Maker s Handbook to Data Science Book PDF

Author : Stylianos Kampakis
Publisher : Apress
Page : 154 pages
File Size : 40,6 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.

Data Science for Economics and Finance

Sergio Consoli,Diego Reforgiato Recupero,Michaela Saisana
Data Science for Economics and Finance Book PDF

Author : Sergio Consoli,Diego Reforgiato Recupero,Michaela Saisana
Publisher : Springer Nature
Page : 357 pages
File Size : 55,7 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.

Management Decision-Making, Big Data and Analytics

Simone Gressel,David J. Pauleen,Nazim Taskin
Management Decision Making Big Data and Analytics Book PDF

Author : Simone Gressel,David J. Pauleen,Nazim Taskin
Publisher : SAGE
Page : 354 pages
File Size : 44,6 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.

It's All Analytics!

Scott Burk,Gary D. Miner
It s All Analytics Book PDF

Author : Scott Burk,Gary D. Miner
Publisher : CRC Press
Page : 186 pages
File Size : 52,6 Mb
Release : 2020-05-25
Category : Medical
ISBN : 9781000067224

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It's All Analytics! by Scott Burk,Gary D. Miner Pdf

It's All Analytics! The Foundations of AI, Big Data and Data Science Landscape for Professionals in Healthcare, Business, and Government (978-0-367-35968-3, 325690) Professionals are challenged each day by a changing landscape of technology and terminology. In recent history, especially in the last 25 years, there has been an explosion of terms and methods that automate and improve decision-making and operations. One term, "analytics," is an overarching description of a compilation of methodologies. But AI (artificial intelligence), statistics, decision science, and optimization, which have been around for decades, have resurged. Also, things like business intelligence, online analytical processing (OLAP) and many, many more have been born or reborn. How is someone to make sense of all this methodology and terminology? This book, the first in a series of three, provides a look at the foundations of artificial intelligence and analytics and why readers need an unbiased understanding of the subject. The authors include the basics such as algorithms, mental concepts, models, and paradigms in addition to the benefits of machine learning. The book also includes a chapter on data and the various forms of data. The authors wrap up this book with a look at the next frontiers such as applications and designing your environment for success, which segue into the topics of the next two books in the series.

Big Data Quantification for Complex Decision-Making

Zhang, Chao,Li, Wentao
Big Data Quantification for Complex Decision Making Book PDF

Author : Zhang, Chao,Li, Wentao
Publisher : IGI Global
Page : 328 pages
File Size : 50,8 Mb
Release : 2024-04-16
Category : Business & Economics
ISBN : 9798369315835

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Big Data Quantification for Complex Decision-Making by Zhang, Chao,Li, Wentao Pdf

Many professionals are facing a monumental challenge: navigating the intricate landscape of information to make impactful choices. The sheer volume and complexity of big data have ushered in a shift, demanding innovative methodologies and frameworks. Big Data Quantification for Complex Decision-Making tackles this challenge head-on, offering a comprehensive exploration of the tools necessary to distill valuable insights from datasets. This book serves as a tool for professionals, researchers, and students, empowering them to not only comprehend the significance of big data in decision-making but also to translate this understanding into real-world decision making. The central objective of the book is to examine the relationship between big data and decision-making. It strives to address multiple objectives, including understanding the intricacies of big data in decision-making, navigating methodological nuances, managing uncertainty adeptly, and bridging theoretical foundations with real-world applications. The book's core aspiration is to provide readers with a comprehensive toolbox, seamlessly integrating theoretical frameworks, practical applications, and forward-thinking perspectives. This equips readers with the means to effectively navigate the data-rich landscape of modern decision-making, fostering a heightened comprehension of strategic big data utilization. Tailored for a diverse audience, this book caters to researchers and academics in data science, decision science, machine learning, artificial intelligence, and related domains.

The Real Work of Data Science

Ron S. Kenett,Thomas C. Redman
The Real Work of Data Science Book PDF

Author : Ron S. Kenett,Thomas C. Redman
Publisher : John Wiley & Sons
Page : 136 pages
File Size : 43,9 Mb
Release : 2019-05-06
Category : Science
ISBN : 9781119570707

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The Real Work of Data Science by Ron S. Kenett,Thomas C. Redman Pdf

The essential guide for data scientists and for leaders who must get more from their data science teams The Economist boldly claims that data are now "the world's most valuable resource." But, as Kenett and Redman so richly describe, unlocking that value requires far more than technical excellence. The Real Work of Data Science explores understanding the problems, dealing with quality issues, building trust with decision makers, putting data science teams in the right organizational spots, and helping companies become data-driven. This is the work that spells the difference between a good data scientist and a great one, between a team that makes marginal contributions and one that drives the business, between a company that gains some value from its data and one in which data truly is "the most valuable resource." "These two authors are world-class experts on analytics, data management, and data quality; they've forgotten more about these topics than most of us will ever know. Their book is pragmatic, understandable, and focused on what really counts. If you want to do data science in any capacity, you need to read it." —Thomas H. Davenport, Distinguished Professor, Babson College and Fellow, MIT Initiative on the Digital Economy "I like your book. The chapters address problems that have faced statisticians for generations, updated to reflect today's issues, such as computational Big Data." —Sir David Cox, Warden of Nuffield College and Professor of Statistics, Oxford University "Data science is critical for competitiveness, for good government, for correct decisions. But what is data science? Kenett and Redman give, by far, the best introduction to the subject I have seen anywhere. They address the critical questions of formulating the right problem, collecting the right data, doing the right analyses, making the right decisions, and measuring the actual impact of the decisions. This book should become required reading in statistics and computer science departments, business schools, analytics institutes and, most importantly, by all business managers." —A. Blanton Godfrey, Joseph D. Moore Distinguished University Professor, Wilson College of Textiles, North Carolina State University

Applied Data Science

Martin Braschler,Thilo Stadelmann,Kurt Stockinger
Applied Data Science Book PDF

Author : Martin Braschler,Thilo Stadelmann,Kurt Stockinger
Publisher : Springer
Page : 465 pages
File Size : 40,8 Mb
Release : 2019-06-13
Category : Computers
ISBN : 9783030118211

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Applied Data Science by Martin Braschler,Thilo Stadelmann,Kurt Stockinger Pdf

This book has two main goals: to define data science through the work of data scientists and their results, namely data products, while simultaneously providing the reader with relevant lessons learned from applied data science projects at the intersection of academia and industry. As such, it is not a replacement for a classical textbook (i.e., it does not elaborate on fundamentals of methods and principles described elsewhere), but systematically highlights the connection between theory, on the one hand, and its application in specific use cases, on the other. With these goals in mind, the book is divided into three parts: Part I pays tribute to the interdisciplinary nature of data science and provides a common understanding of data science terminology for readers with different backgrounds. These six chapters are geared towards drawing a consistent picture of data science and were predominantly written by the editors themselves. Part II then broadens the spectrum by presenting views and insights from diverse authors – some from academia and some from industry, ranging from financial to health and from manufacturing to e-commerce. Each of these chapters describes a fundamental principle, method or tool in data science by analyzing specific use cases and drawing concrete conclusions from them. The case studies presented, and the methods and tools applied, represent the nuts and bolts of data science. Finally, Part III was again written from the perspective of the editors and summarizes the lessons learned that have been distilled from the case studies in Part II. The section can be viewed as a meta-study on data science across a broad range of domains, viewpoints and fields. Moreover, it provides answers to the question of what the mission-critical factors for success in different data science undertakings are. The book targets professionals as well as students of data science: first, practicing data scientists in industry and academia who want to broaden their scope and expand their knowledge by drawing on the authors’ combined experience. Second, decision makers in businesses who face the challenge of creating or implementing a data-driven strategy and who want to learn from success stories spanning a range of industries. Third, students of data science who want to understand both the theoretical and practical aspects of data science, vetted by real-world case studies at the intersection of academia and industry.

Data Science for Business

Foster Provost,Tom Fawcett
Data Science for Business Book PDF

Author : Foster Provost,Tom Fawcett
Publisher : "O'Reilly Media, Inc."
Page : 414 pages
File Size : 42,5 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

Big Data on Campus

Karen L. Webber,Henry Y. Zheng
Big Data on Campus Book PDF

Author : Karen L. Webber,Henry Y. Zheng
Publisher : Johns Hopkins University Press
Page : 337 pages
File Size : 41,7 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

Be Data Driven

Jordan Morrow
Be Data Driven Book PDF

Author : Jordan Morrow
Publisher : Kogan Page Publishers
Page : 241 pages
File Size : 44,7 Mb
Release : 2022-08-03
Category : Business & Economics
ISBN : 9781398606555

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Be Data Driven by Jordan Morrow Pdf

Make any team or business data driven with this practical guide to overcoming common challenges and creating a data culture. Businesses are increasingly focusing on their data and analytics strategy, but a data-driven culture grounded in evidence-based decision making can be difficult to achieve. Be Data Driven outlines a step-by-step roadmap to building a data-driven organization or team, beginning with deciding on outcomes and a strategy before moving onto investing in technology and upskilling where necessary. This practical guide explains what it means to be a data-driven organization and explores which technologies are advancing data and analytics. Crucially, it also examines the most common challenges to becoming data driven, from a foundational skills gap to issues with leadership and strategy and the impact of organizational culture. With case studies of businesses who have successfully used data, Be Data Driven shows managers, leaders and data professionals how to address hurdles, encourage a data culture and become truly data driven.

Becoming a Data Head

Alex J. Gutman,Jordan Goldmeier
Becoming a Data Head Book PDF

Author : Alex J. Gutman,Jordan Goldmeier
Publisher : John Wiley & Sons
Page : 235 pages
File Size : 43,8 Mb
Release : 2021-04-13
Category : Business & Economics
ISBN : 9781119741718

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Becoming a Data Head by Alex J. Gutman,Jordan Goldmeier Pdf

"Turn yourself into a Data Head. You'll become a more valuable employee and make your organization more successful." Thomas H. Davenport, Research Fellow, Author of Competing on Analytics, Big Data @ Work, and The AI Advantage You've heard the hype around data—now get the facts. In Becoming a Data Head: How to Think, Speak, and Understand Data Science, Statistics, and Machine Learning, award-winning data scientists Alex Gutman and Jordan Goldmeier pull back the curtain on data science and give you the language and tools necessary to talk and think critically about it. You'll learn how to: Think statistically and understand the role variation plays in your life and decision making Speak intelligently and ask the right questions about the statistics and results you encounter in the workplace Understand what's really going on with machine learning, text analytics, deep learning, and artificial intelligence Avoid common pitfalls when working with and interpreting data Becoming a Data Head is a complete guide for data science in the workplace: covering everything from the personalities you’ll work with to the math behind the algorithms. The authors have spent years in data trenches and sought to create a fun, approachable, and eminently readable book. Anyone can become a Data Head—an active participant in data science, statistics, and machine learning. Whether you're a business professional, engineer, executive, or aspiring data scientist, this book is for you.

Business Analytics

Walter R. Paczkowski
Business Analytics Book PDF

Author : Walter R. Paczkowski
Publisher : Springer Nature
Page : 416 pages
File Size : 55,7 Mb
Release : 2022-01-03
Category : Business & Economics
ISBN : 9783030870232

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Business Analytics by Walter R. Paczkowski Pdf

This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems. These are a foundational understanding of: 1. statistical, econometric, and machine learning techniques; 2. data handling capabilities; 3. at least one programming language. Practical in orientation, the volume offers illustrative case studies throughout and examples using Python in the context of Jupyter notebooks. Covered topics include demand measurement and forecasting, predictive modeling, pricing analytics, customer satisfaction assessment, market and advertising research, and new product development and research. This volume will be useful to business data analysts, data scientists, and market research professionals, as well as aspiring practitioners in business data analytics. It can also be used in colleges and universities offering courses and certifications in business data analytics, data science, and market research.

The Data Driven Leader

Jenny Dearborn,David Swanson
The Data Driven Leader Book PDF

Author : Jenny Dearborn,David Swanson
Publisher : John Wiley & Sons
Page : 272 pages
File Size : 42,8 Mb
Release : 2017-11-06
Category : Business & Economics
ISBN : 9781119382201

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The Data Driven Leader by Jenny Dearborn,David Swanson Pdf

Data is your most valuable leadership asset—here's how to use it The Data Driven Leader presents a clear, accessible guide to solving important leadership challenges through human resources-focused and other data analytics. This engaging book shows you how to transform the HR function and overall organizational effectiveness by using data to make decisions grounded in facts vs. opinions, identify root causes behind your company’s thorniest problems and move toward a winning, future-focused business strategy. Realistic and actionable, this book tells the story of a successful sales executive who, after leading an analytics-driven turnaround (in Data Driven, this book’s predecessor), faces a new turnaround challenge as chief human resources officer. Each chapter features insightful commentary and practical notes on the points the story raises, guiding you to put HR analytics into action in your organization. HR and other leaders cannot afford to overlook the power and competitive advantages of data-driven decision-making and strategies. This book reflects the growing trend of CEOs choosing analytics-minded business leaders to head HR, at a time when workplaces everywhere face game-changing forces including automation, robotics and artificial intelligence. It is urgent that human resources leaders embrace analytics, not only to remain professionally relevant but also to help their organizations successfully navigate this digital transformation. HR professionals can and must: Understand essential data science principles and corporate analytics models Identify and execute effective data analytics initiatives Boost HR and company productivity and performance with metrics that matter Shape an analytics-centric culture that generates data driven leaders Most organizations capture and report data, but data is useless without analysis that leads to action. The Data Driven Leader shows you how to use this tremendous asset to lead your organization higher.