Data Science for Business
Data Science for Business

Author: Foster Provost

Publisher: "O'Reilly Media, Inc."

Published: 2013-07-27

Total Pages: 506

ISBN-13: 144937428X

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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

From Science to Startup
From Science to Startup

Author: Anil Sethi

Publisher: Springer

Published: 2016-04-13

Total Pages: 249

ISBN-13: 3319304240

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This book charts the experiences, pitfalls and knowledge behind leading scientific ideas to successful startups. Written by one of Switzerland's top serial entrepreneurs, this book is a must-read for scientists and academicians who want to see their idea turn into a product and change the market. It is also pertinent for finance and business professionals who aspire to become technology entrepreneurs. Starting with personal qualities of an entrepreneur, Anil Sethi discusses successful ideas, technology evaluation, team formation, patents and investor expectations. To guide the entrepreneur, this book also analyzes deal closing, equity conversion and ideal exit strategies to follow. Ultimately Anil Sethi reveals the 'inside track' which helps understand what drives entrepreneurs and what they wouldn't admit.

Data Science for Entrepreneurship
Data Science for Entrepreneurship

Author: Werner Liebregts

Publisher: Springer Nature

Published: 2023-03-23

Total Pages: 532

ISBN-13: 303119554X

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The fast-paced technological development and the plethora of data create numerous opportunities waiting to be exploited by entrepreneurs. This book provides a detailed, yet practical, introduction to the fundamental principles of data science and how entrepreneurs and would-be entrepreneurs can take advantage of it. It walks the reader through sections on data engineering, and data analytics as well as sections on data entrepreneurship and data use in relation to society. The book also offers ways to close the research and practice gaps between data science and entrepreneurship. By having read this book, students of entrepreneurship courses will be better able to commercialize data-driven ideas that may be solutions to real-life problems. Chapters contain detailed examples and cases for a better understanding. Discussion points or questions at the end of each chapter help to deeply reflect on the learning material.

Entrepreneurship and Big Data
Entrepreneurship and Big Data

Author: Meghna Chhabra

Publisher: CRC Press

Published: 2021-09-30

Total Pages: 301

ISBN-13: 1000455696

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The digital age has transformed business opportunities and strategies in a resolutely practical and data-driven project universe. This book is a comprehensive and analytical source on entrepreneurship and Big Data that prospective entrepreneurs must know before embarking upon an entrepreneurial journey in this present age of digital transformation. This book provides an overview of the various aspects of entrepreneurship, function, and contemporary forms. It covers a real-world understanding of how the entrepreneurial world works and the required new analytics thinking and computational skills. It also encompasses the essential elements needed when starting an entrepreneurial journey and offers inspirational case studies from key industry leaders. Ideal reading for aspiring entrepreneurs, Entrepreneurship and Big Data: The Digital Revolution is also useful to students, academicians, researchers, and practitioners.

Big Data for Entrepreneurship and Sustainable Development
Big Data for Entrepreneurship and Sustainable Development

Author: Mohammed El Amine Abdelli

Publisher: CRC Press

Published: 2021-12-09

Total Pages: 223

ISBN-13: 1000454401

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This book provides insight for researchers and decision-makers on the application of data in the entrepreneurship and sustainable development sector. This book covers how Big Data for Industry 4.0 and entrepreneurship are effective in resolving business, social, and economic problems. The book discusses how entrepreneurs use Big Data to cut costs and minimize the waste of time. It offers how using Big Data can increase efficiency, enables the studying of competitors, can improve the pricing of products, increase sales and loyalty, and can ensure the right people are hired. The book presents how decision-makers can make use of Big Data to resolve economic and social problems. Analyze the development of the economy and enhance the business climate. This book is for researchers, PhD students, and entrepreneurs and can also be of interest for transforming governments as well as businesses.

Lean Analytics
Lean Analytics

Author: Alistair Croll

Publisher: "O'Reilly Media, Inc."

Published: 2024-02-23

Total Pages: 403

ISBN-13: 1098168151

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Whether you're a startup founder trying to disrupt an industry or an entrepreneur trying to provoke change from within, your biggest challenge is creating a product people actually want. Lean Analytics steers you in the right direction. This book shows you how to validate your initial idea, find the right customers, decide what to build, how to monetize your business, and how to spread the word. Packed with more than thirty case studies and insights from over a hundred business experts, Lean Analytics provides you with hard-won, real-world information no entrepreneur can afford to go without. Understand Lean Startup, analytics fundamentals, and the data-driven mindset Look at six sample business models and how they map to new ventures of all sizes Find the One Metric That Matters to you Learn how to draw a line in the sand, so you'll know it's time to move forward Apply Lean Analytics principles to large enterprises and established products

Entrepreneurship for Scientists and Engineers
Entrepreneurship for Scientists and Engineers

Author: Kathleen R. Allen

Publisher: Pearson

Published: 2010

Total Pages: 0

ISBN-13: 9780132357272

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KEY BENEFIT Essential business lessons for turning today's scientists and engineers into entrepreneurs in new technology companies. In today's global and interconnected world, students with a science or engineering background have ample opportunity to mesh their technical know-how with the free market. Yet, these same students lack the basic business skills to make competent business decisions. This book seeks to make students' first experience with entrepreneurship interesting and useful. KEY TOPICS Technology Entrepreneurship for Scientists and Engineers; Developing and Protecting Intellectual Property; Technology Entrepreneurship Strategy; Start-up Financial Strategy As the source of new discoveries and technologies, scientists and engineers are uniquely positioned to launch new business ventures based on cutting-edge discoveries. This book will teach those with no prior training how to start a company and grow their business through marketing and astute team building techniques.

Entrepreneurship for Creative Scientists
Entrepreneurship for Creative Scientists

Author: Dawood Parker

Publisher:

Published: 2018-05-23

Total Pages: 130

ISBN-13: 9780750318570

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Being a scientist has changed dramatically in recent times. Through patenting and commercialization, scientists today can develop their work beyond a publication in a learned journal. Indeed, universities and governments are encouraging today's scientists and engineers to break their research out of the laboratory and into the commercial world. However, doing so is complicated and can be daunting for those more used to a research seminar than a boardroom. Start-ups are journeys into uncertainty and entrepreneurs are individuals who are comfortable with uncertainty, thrive on challenges and are prepared to take risks. This book, written by experienced scientists and entrepreneurs, deals with businesses started by scientists based on innovation and sets out to clarify for scientists and engineers the steps necessary to take an idea along the path to commercialization and maximize the potential for success, regardless of the path taken. The difference between a scientist and an entrepreneur is discussed as is the consequence to an enterprise of misunderstanding this difference. The various roles in which an entrepreneur can act are discussed, as are the types of business that a scientist can start. The concept of patent protection is explained as is the process of applying for a patent. The authors take the reader through the need for a business plan and give examples of how such a plan might look. Fundraising is discussed at length with attention focussed on sources of funding and the technique of 'pitching' for funds. Managing a start-up is explored and the function and roles within the management team are discussed.

Big Data, Data Mining, and Machine Learning
Big Data, Data Mining, and Machine Learning

Author: Jared Dean

Publisher: John Wiley & Sons

Published: 2014-05-07

Total Pages: 293

ISBN-13: 1118920708

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With big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes: A complete overview of big data and its notable characteristics Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases Comprehensive coverage of data mining, text analytics, and machine learning algorithms A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.

The Decision Maker's Handbook to Data Science
The Decision Maker's Handbook to Data Science

Author: Stylianos Kampakis

Publisher: Apress

Published: 2019-11-26

Total Pages: 154

ISBN-13: 1484254945

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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.