Data Science For Entrepreneurship

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Data Science for Business

Author : Foster Provost
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 144937428X
Total Pages : 414 pages
Book Rating : 4.4/5 (493 download)

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Book Synopsis Data Science for Business by : Foster Provost

Download or read book Data Science for Business written by Foster Provost and published by "O'Reilly Media, Inc.". This book was released on 2013-07-27 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions

Author : Matt Taddy
Publisher : McGraw Hill Professional
ISBN 13 : 1260452786
Total Pages : 384 pages
Book Rating : 4.2/5 (64 download)

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Book Synopsis Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions by : Matt Taddy

Download or read book Business Data Science: Combining Machine Learning and Economics to Optimize, Automate, and Accelerate Business Decisions written by Matt Taddy and published by McGraw Hill Professional. This book was released on 2019-08-23 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: Publisher's Note: Products purchased from Third Party sellers are not guaranteed by the publisher for quality, authenticity, or access to any online entitlements included with the product. Use machine learning to understand your customers, frame decisions, and drive value The business analytics world has changed, and Data Scientists are taking over. Business Data Science takes you through the steps of using machine learning to implement best-in-class business data science. Whether you are a business leader with a desire to go deep on data, or an engineer who wants to learn how to apply Machine Learning to business problems, you’ll find the information, insight, and tools you need to flourish in today’s data-driven economy. You’ll learn how to: •Use the key building blocks of Machine Learning: sparse regularization, out-of-sample validation, and latent factor and topic modeling•Understand how use ML tools in real world business problems, where causation matters more that correlation•Solve data science programs by scripting in the R programming language Today’s business landscape is driven by data and constantly shifting. Companies live and die on their ability to make and implement the right decisions quickly and effectively. Business Data Science is about doing data science right. It’s about the exciting things being done around Big Data to run a flourishing business. It’s about the precepts, principals, and best practices that you need know for best-in-class business data science.

Data Science for Business and Decision Making

Author : Luiz Paulo Fávero
Publisher : Academic Press
ISBN 13 : 0128112174
Total Pages : 1240 pages
Book Rating : 4.1/5 (281 download)

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Book Synopsis Data Science for Business and Decision Making by : Luiz Paulo Fávero

Download or read book Data Science for Business and Decision Making written by Luiz Paulo Fávero and published by Academic Press. This book was released on 2019-04-11 with total page 1240 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 With R

Author : Jeffrey S. Saltz
Publisher : SAGE Publications, Incorporated
ISBN 13 : 1544370482
Total Pages : 423 pages
Book Rating : 4.5/5 (443 download)

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Book Synopsis Data Science for Business With R by : Jeffrey S. Saltz

Download or read book Data Science for Business With R written by Jeffrey S. Saltz and published by SAGE Publications, Incorporated. This book was released on 2021-02-03 with total page 423 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science for Business with R, written by Jeffrey S. Saltz and Jeffrey M. Stanton, focuses on the concepts foundational for students starting a business analytics or data science degree program. To keep the book practical and applied, the authors feature a running case using a global airline business’s customer survey dataset to illustrate how to turn data in business decisions, in addition to numerous examples throughout. To aid in usability beyond the classroom, the text features full integration of freely-available R and RStudio software, one of the most popular data science tools available. Designed for students with little to no experience in related areas like computer science, the book chapters follow a logical order from introduction and installation of R and RStudio, working with data architecture, undertaking data collection, performing data analysis, and transitioning to data archiving and presentation. Each chapter follows a familiar structure, starting with learning objectives and background, following the basic steps of functions alongside simple examples, applying these functions to the case study, and ending with chapter challenge questions, sources, and a list of R functions so students know what to expect in each step of their data science course. Data Science for Business with R provides readers with a straightforward and applied guide to this new and evolving field.

Data Science and Digital Business

Author : Fausto Pedro García Márquez
Publisher : Springer
ISBN 13 : 3319956515
Total Pages : 316 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Data Science and Digital Business by : Fausto Pedro García Márquez

Download or read book Data Science and Digital Business written by Fausto Pedro García Márquez and published by Springer. This book was released on 2019-01-04 with total page 316 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book combines the analytic principles of digital business and data science with business practice and big data. The interdisciplinary, contributed volume provides an interface between the main disciplines of engineering and technology and business administration. Written for managers, engineers and researchers who want to understand big data and develop new skills that are necessary in the digital business, it not only discusses the latest research, but also presents case studies demonstrating the successful application of data in the digital business.

Data Science for Business Professionals

Author : Probyto Data Science and Consulting Pvt. Ltd.
Publisher : BPB Publications
ISBN 13 : 9389423287
Total Pages : 368 pages
Book Rating : 4.3/5 (894 download)

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Book Synopsis Data Science for Business Professionals by : Probyto Data Science and Consulting Pvt. Ltd.

Download or read book Data Science for Business Professionals written by Probyto Data Science and Consulting Pvt. Ltd. and published by BPB Publications. This book was released on 2020-05-06 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Primer into the multidisciplinary world of Data Science KEY FEATURESÊÊ - Explore and use the key concepts of Statistics required to solve data science problems - Use Docker, Jenkins, and Git for Continuous Development and Continuous Integration of your web app - Learn how to build Data Science solutions with GCP and AWS DESCRIPTIONÊ The book will initially explain the What-Why of Data Science and the process of solving a Data Science problem. The fundamental concepts of Data Science, such as Statistics, Machine Learning, Business Intelligence, Data pipeline, and Cloud Computing, will also be discussed. All the topics will be explained with an example problem and will show how the industry approaches to solve such a problem. The book will pose questions to the learners to solve the problems and build the problem-solving aptitude and effectively learn. The book uses Mathematics wherever necessary and will show you how it is implemented using Python with the help of an example dataset.Ê WHAT WILL YOU LEARNÊÊ - Understand the multi-disciplinary nature of Data Science - Get familiar with the key concepts in Mathematics and Statistics - Explore a few key ML algorithms and their use cases - Learn how to implement the basics of Data Pipelines - Get an overview of Cloud Computing & DevOps - Learn how to create visualizations using Tableau WHO THIS BOOK IS FORÊ This book is ideal for Data Science enthusiasts who want to explore various aspects of Data Science. Useful for Academicians, Business owners, and Researchers for a quick reference on industrial practices in Data Science.Ê TABLE OF CONTENTS 1. Data Science in Practice 2. Mathematics Essentials 3. Statistics Essentials 4. Exploratory Data Analysis 5. Data preprocessing 6. Feature Engineering 7. Machine learning algorithms 8. Productionizing ML models 9. Data Flows in Enterprises 10. Introduction to Databases 11. Introduction to Big Data 12. DevOps for Data Science 13. Introduction to Cloud Computing 14. Deploy Model to Cloud 15. Introduction to Business IntelligenceÊ 16. Data Visualization Tools 17. Industry Use Case 1 Ð FormAssist 18. Industry Use Case 2 Ð PeopleReporter 19. Data Science Learning Resources 20. Do It Your Self Challenges 21. MCQs for Assessments

Big Data MBA

Author : Bill Schmarzo
Publisher : John Wiley & Sons
ISBN 13 : 1119238846
Total Pages : 312 pages
Book Rating : 4.1/5 (192 download)

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Book Synopsis Big Data MBA by : Bill Schmarzo

Download or read book Big Data MBA written by Bill Schmarzo and published by John Wiley & Sons. This book was released on 2015-12-11 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integrate big data into business to drive competitive advantage and sustainable success Big Data MBA brings insight and expertise to leveraging big data in business so you can harness the power of analytics and gain a true business advantage. Based on a practical framework with supporting methodology and hands-on exercises, this book helps identify where and how big data can help you transform your business. You'll learn how to exploit new sources of customer, product, and operational data, coupled with advanced analytics and data science, to optimize key processes, uncover monetization opportunities, and create new sources of competitive differentiation. The discussion includes guidelines for operationalizing analytics, optimal organizational structure, and using analytic insights throughout your organization's user experience to customers and front-end employees alike. You'll learn to “think like a data scientist” as you build upon the decisions your business is trying to make, the hypotheses you need to test, and the predictions you need to produce. Business stakeholders no longer need to relinquish control of data and analytics to IT. In fact, they must champion the organization's data collection and analysis efforts. This book is a primer on the business approach to analytics, providing the practical understanding you need to convert data into opportunity. Understand where and how to leverage big data Integrate analytics into everyday operations Structure your organization to drive analytic insights Optimize processes, uncover opportunities, and stand out from the rest Help business stakeholders to “think like a data scientist” Understand appropriate business application of different analytic techniques If you want data to transform your business, you need to know how to put it to use. Big Data MBA shows you how to implement big data and analytics to make better decisions.

Data Analytics in Marketing, Entrepreneurship, and Innovation

Author : Mounir Kehal
Publisher : CRC Press
ISBN 13 : 0429591683
Total Pages : 193 pages
Book Rating : 4.4/5 (295 download)

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Book Synopsis Data Analytics in Marketing, Entrepreneurship, and Innovation by : Mounir Kehal

Download or read book Data Analytics in Marketing, Entrepreneurship, and Innovation written by Mounir Kehal and published by CRC Press. This book was released on 2021-01-12 with total page 193 pages. Available in PDF, EPUB and Kindle. Book excerpt: Innovation based in data analytics is a contemporary approach to developing empirically supported advances that encourage entrepreneurial activity inspired by novel marketing inferences. Data Analytics in Marketing, Entrepreneurship, and Innovation covers techniques, processes, models, tools, and practices for creating business opportunities through data analytics. It features case studies that provide realistic examples of applications. This multifaceted examination of data analytics looks at: Business analytics Applying predictive analytics Using discrete choice analysis for decision-making Marketing and customer analytics Developing new products Technopreneurship Disruptive versus incremental innovation The book gives researchers and practitioners insight into how data analytics is used in the areas of innovation, entrepreneurship, and marketing. Innovation analytics helps identify opportunities to develop new products and services, and improve existing methods of product manufacturing and service delivery. Entrepreneurial analytics facilitates the transformation of innovative ideas into strategy and helps entrepreneurs make critical decisions based on data-driven techniques. Marketing analytics is used in collecting, managing, assessing, and analyzing marketing data to predict trends, investigate customer preferences, and launch campaigns.

Data Science for Entrepreneurship

Author : Werner Liebregts
Publisher : Springer Nature
ISBN 13 : 303119554X
Total Pages : 532 pages
Book Rating : 4.0/5 (311 download)

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Book Synopsis Data Science for Entrepreneurship by : Werner Liebregts

Download or read book Data Science for Entrepreneurship written by Werner Liebregts and published by Springer Nature. This book was released on 2023-03-23 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Applied Data Science

Author : Martin Braschler
Publisher : Springer
ISBN 13 : 3030118215
Total Pages : 465 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Applied Data Science by : Martin Braschler

Download or read book Applied Data Science written by Martin Braschler and published by Springer. This book was released on 2019-06-13 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Recent Developments in Data Science and Business Analytics

Author : Madjid Tavana
Publisher : Springer
ISBN 13 : 3319727451
Total Pages : 505 pages
Book Rating : 4.3/5 (197 download)

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Book Synopsis Recent Developments in Data Science and Business Analytics by : Madjid Tavana

Download or read book Recent Developments in Data Science and Business Analytics written by Madjid Tavana and published by Springer. This book was released on 2018-03-27 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains.

Data Smart

Author : John W. Foreman
Publisher : John Wiley & Sons
ISBN 13 : 1118839862
Total Pages : 432 pages
Book Rating : 4.1/5 (188 download)

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Book Synopsis Data Smart by : John W. Foreman

Download or read book Data Smart written by John W. Foreman and published by John Wiley & Sons. This book was released on 2013-10-31 with total page 432 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Science gets thrown around in the press like it'smagic. Major retailers are predicting everything from when theircustomers are pregnant to when they want a new pair of ChuckTaylors. It's a brave new world where seemingly meaningless datacan be transformed into valuable insight to drive smart businessdecisions. But how does one exactly do data science? Do you have to hireone of these priests of the dark arts, the "data scientist," toextract this gold from your data? Nope. Data science is little more than using straight-forward steps toprocess raw data into actionable insight. And in DataSmart, author and data scientist John Foreman will show you howthat's done within the familiar environment of aspreadsheet. Why a spreadsheet? It's comfortable! You get to look at the dataevery step of the way, building confidence as you learn the tricksof the trade. Plus, spreadsheets are a vendor-neutral place tolearn data science without the hype. But don't let the Excel sheets fool you. This is a book forthose serious about learning the analytic techniques, the math andthe magic, behind big data. Each chapter will cover a different technique in aspreadsheet so you can follow along: Mathematical optimization, including non-linear programming andgenetic algorithms Clustering via k-means, spherical k-means, and graphmodularity Data mining in graphs, such as outlier detection Supervised AI through logistic regression, ensemble models, andbag-of-words models Forecasting, seasonal adjustments, and prediction intervalsthrough monte carlo simulation Moving from spreadsheets into the R programming language You get your hands dirty as you work alongside John through eachtechnique. But never fear, the topics are readily applicable andthe author laces humor throughout. You'll even learnwhat a dead squirrel has to do with optimization modeling, whichyou no doubt are dying to know.

Lean Analytics

Author : Alistair Croll
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1098168151
Total Pages : 403 pages
Book Rating : 4.0/5 (981 download)

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Book Synopsis Lean Analytics by : Alistair Croll

Download or read book Lean Analytics written by Alistair Croll and published by "O'Reilly Media, Inc.". This book was released on 2024-02-23 with total page 403 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Business Analytics

Author : Walter R. Paczkowski
Publisher : Springer Nature
ISBN 13 : 3030870235
Total Pages : 416 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Business Analytics by : Walter R. Paczkowski

Download or read book Business Analytics written by Walter R. Paczkowski and published by Springer Nature. This book was released on 2022-01-03 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

From Science to Startup

Author : Anil Sethi
Publisher : Springer
ISBN 13 : 3319304240
Total Pages : 243 pages
Book Rating : 4.3/5 (193 download)

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Book Synopsis From Science to Startup by : Anil Sethi

Download or read book From Science to Startup written by Anil Sethi and published by Springer. This book was released on 2016-04-13 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

How to Talk to Data Scientists

Author : Jeremy Elser
Publisher : Business Expert Press
ISBN 13 : 1637420986
Total Pages : 107 pages
Book Rating : 4.6/5 (374 download)

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Book Synopsis How to Talk to Data Scientists by : Jeremy Elser

Download or read book How to Talk to Data Scientists written by Jeremy Elser and published by Business Expert Press. This book was released on 2021-08-05 with total page 107 pages. Available in PDF, EPUB and Kindle. Book excerpt: Every major company has or will soon have a data science program. Most fail, expensively, imperiling their executive sponsors. Unfortunately, executives have been misled to focus on the latest buzzwords. Although buzzwords change— big data, data science, machine learning, deep learning, and artificial intelligence –the distraction from fundamentals manifests as a predictable trajectory from exuberant program launch, to stagnation, to awkward decommissioning. After architecting data science programs at over a dozen companies, across sectors and scales, Dr. Elser has formulated a reliable framework for successful data science programs. Surprisingly, software and algorithms are secondary. Rather, the key is understanding how the available data aligns to the problem to be solved. The business executive understands the problem sufficiently to enforce this alignment, while data scientists act on it. But executives tend to underestimate their role and thereby fail to construct the necessary connective tissue with their data scientists. This book provides business executives with a concrete exercise, populating a “Master Table,” accessible to nontechnical managers and data scientists, which serves as the connective tissue between them. Rather than teach a diluted version of data science, this book describes how to start projects and how to detect and fix problems—the moments when leadership is critical. Insights are provided through real world examples, including a Playbook featuring common projects. The intended audience is executives (C-suite through VP). However, ambitious mid-level managers and data scientists will also benefit.

The Data Industry

Author : Chunlei Tang
Publisher : John Wiley & Sons
ISBN 13 : 111913840X
Total Pages : 217 pages
Book Rating : 4.1/5 (191 download)

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Book Synopsis The Data Industry by : Chunlei Tang

Download or read book The Data Industry written by Chunlei Tang and published by John Wiley & Sons. This book was released on 2016-06-13 with total page 217 pages. Available in PDF, EPUB and Kindle. Book excerpt: Provides an introduction of the data industry to the field of economics This book bridges the gap between economics and data science to help data scientists understand the economics of big data, and enable economists to analyze the data industry. It begins by explaining data resources and introduces the data asset. This book defines a data industry chain, enumerates data enterprises’ business models versus operating models, and proposes a mode of industrial development for the data industry. The author describes five types of enterprise agglomerations, and multiple industrial cluster effects. A discussion on the establishment and development of data industry related laws and regulations is provided. In addition, this book discusses several scenarios on how to convert data driving forces into productivity that can then serve society. This book is designed to serve as a reference and training guide for ata scientists, data-oriented managers and executives, entrepreneurs, scholars, and government employees. Defines and develops the concept of a “Data Industry,” and explains the economics of data to data scientists and statisticians Includes numerous case studies and examples from a variety of industries and disciplines Serves as a useful guide for practitioners and entrepreneurs in the business of data technology The Data Industry: The Business and Economics of Information and Big Data is a resource for practitioners in the data science industry, government, and students in economics, business, and statistics. CHUNLEI TANG, Ph.D., is a research fellow at Harvard University. She is the co-founder of Fudan’s Institute for Data Industry and proposed the concept of the “data industry”. She received a Ph.D. in Computer and Software Theory in 2012 and a Master of Software Engineering in 2006 from Fudan University, Shanghai, China.