Big Data MBA

This book is a primer on the business approach to analytics, providing the practical understanding you need to convert data into opportunity.

Author: Bill Schmarzo

Publisher: John Wiley & Sons

ISBN: 9781119181118

Category: Computers

Page: 312

View: 241

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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.
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Big Data MBA

Driving Business Strategies with Data Science Bill Schmarzo. Big Data MBA Driving Business Strategies with Data Science Bill Schmarzo Big Data MBA: Driving Business Strategies with Data Science Published. Title Page.

Author: Bill Schmarzo

Publisher: John Wiley & Sons

ISBN: 9781119238843

Category: Computers

Page: 312

View: 778

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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.
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The The Economics of Data Analytics and Digital Transformation

A comprehensive guide for seasoned business leaders who struggle with where and how to exploit the economics of data and analytics to gain true value from data, accelerate company operations through AI, and guide their digital ...

Author: Bill Schmarzo

Publisher: Packt Publishing Ltd

ISBN: 9781800569133

Category: Computers

Page: 260

View: 113

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A comprehensive guide for seasoned business leaders who struggle with where and how to exploit the economics of data and analytics to gain true value from data, accelerate company operations through AI, and guide their digital transformation.
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97 Things About Ethics Everyone in Data Science Should Know

As a student in UC Berkeley's Master of Information and Data Science (MIDS) program, Anna is rigorously pursuing the ... in his courses Big Data MBA: Driving Business Strategies with Data Science and Thinking Like a Data Scientist.

Author: Bill Franks

Publisher: "O'Reilly Media, Inc."

ISBN: 9781492072614

Category: Computers

Page: 346

View: 586

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Most of the high-profile cases of real or perceived unethical activity in data science aren’t matters of bad intent. Rather, they occur because the ethics simply aren’t thought through well enough. Being ethical takes constant diligence, and in many situations identifying the right choice can be difficult. In this in-depth book, contributors from top companies in technology, finance, and other industries share experiences and lessons learned from collecting, managing, and analyzing data ethically. Data science professionals, managers, and tech leaders will gain a better understanding of ethics through powerful, real-world best practices. Articles include: Ethics Is Not a Binary Concept—Tim Wilson How to Approach Ethical Transparency—Rado Kotorov Unbiased ≠ Fair—Doug Hague Rules and Rationality—Christof Wolf Brenner The Truth About AI Bias—Cassie Kozyrkov Cautionary Ethics Tales—Sherrill Hayes Fairness in the Age of Algorithms—Anna Jacobson The Ethical Data Storyteller—Brent Dykes Introducing Ethicize™, the Fully AI-Driven Cloud-Based Ethics Solution!—Brian O’Neill Be Careful with "Decisions of the Heart"—Hugh Watson Understanding Passive Versus Proactive Ethics—Bill Schmarzo
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Digital Transformation for a Sustainable Society in the 21st Century

IFAC-PapersOnLine 50(1), 11719–11724 (2017) 59. SAS: Semma. https://www.sas.com/engb/software/analytics-overview.html. Accessed 10 Apr 2019 60. Schmarzo, B.: Big Data MBA: Driving Business Strategies with Data Science.

Author: Ilias O. Pappas

Publisher: Springer Nature

ISBN: 9783030293741

Category: Computers

Page: 811

View: 889

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This book constitutes the proceedings of the 18th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2019, held in Trondheim, Norway, in September 2019. The total of 61 full and 4 short papers presented in this volume were carefully reviewed and selected from 138 submissions. The papers were organized in topical sections named: e-business; big data analytics, open science and open data; artificial intelligence and internet of things; smart cities and smart homes, social media and analytics; digital governance; digital divide and social inclusion; learning and education; security in digital environments; modelling and managing the digital enterprise; digital innovation and business transformation; and online communities.
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Navigating the Labyrinth

Data Stewardship: An Actionable Guide to Effective Data Management and Data Governance. ... Data Driven: Profiting from Your Most Important Business Asset. ... Big Data MBA: Driving Business Strategies with Data Science. Wiley, 2015.

Author: Laura Sebastian-Coleman

Publisher: Technics Publications

ISBN: 9781634623773

Category: Computers

Page: 208

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An Executive Guide to Data Management
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Advanced Information Networking and Applications

65, 1052–1058 (2015). http://www.sciencedirect.com/science/article/pii/ S1877050915028835. Accessed 18 Feb 2016 Schmarzo, B.: Driving Business Strategies with Data Science Big Data MBA (2016). https:// ...

Author: Leonard Barolli

Publisher: Springer

ISBN: 9783030150327

Category: Technology & Engineering

Page: 1357

View: 876

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The aim of the book is to provide latest research findings, innovative research results, methods and development techniques from both theoretical and practical perspectives related to the emerging areas of information networking and applications. Networks of today are going through a rapid evolution and there are many emerging areas of information networking and their applications. Heterogeneous networking supported by recent technological advances in low power wireless communications along with silicon integration of various functionalities such as sensing, communications, intelligence and actuations are emerging as a critically important disruptive computer class based on a new platform, networking structure and interface that enable novel, low cost and high volume applications. Several of such applications have been difficult to realize because of many interconnections problems. To fulfill their large range of applications different kinds of networks need to collaborate and wired and next generation wireless systems should be integrated in order to develop high performance computing solutions to problems arising from the complexities of these networks. This book covers the theory, design and applications of computer networks, distributed computing and information systems.
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Big Data Science in Finance

This valuable book: Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers ...

Author: Irene Aldridge

Publisher: John Wiley & Sons

ISBN: 9781119602989

Category: Computers

Page: 336

View: 272

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Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Data science has fundamentally changed Wall Street—applied mathematics and software code are increasingly driving finance and investment-decision tools. Big Data Science in Finance examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative finance, and quantitative methodology author Irene Aldridge help readers harness the power of Big Data. Comprehensive in scope, this book offers in-depth instruction on how to separate signal from noise, how to deal with missing data values, and how to utilize Big Data techniques in decision-making. Key topics include data clustering, data storage optimization, Big Data dynamics, Monte Carlo methods and their applications in Big Data analysis, and more. This valuable book: Provides a complete account of Big Data that includes proofs, step-by-step applications, and code samples Explains the difference between Principal Component Analysis (PCA) and Singular Value Decomposition (SVD) Covers vital topics in the field in a clear, straightforward manner Compares, contrasts, and discusses Big Data and Small Data Includes Cornell University-tested educational materials such as lesson plans, end-of-chapter questions, and downloadable lecture slides Big Data Science in Finance: Mathematics and Applications is an important, up-to-date resource for students in economics, econometrics, finance, applied mathematics, industrial engineering, and business courses, and for investment managers, quantitative traders, risk and portfolio managers, and other financial practitioners.
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Succeeding with AI

How to make AI work for your business Veljko Krunic ... Available from: https://www.sas.com/en_us/home.html International Business Machines Corporation. ... Schmarzo B. Big data MBA: Driving business strategies with data science.

Author: Veljko Krunic

Publisher: Manning Publications

ISBN: 9781617296932

Category: Business & Economics

Page: 288

View: 482

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Summary Companies small and large are initiating AI projects, investing vast sums of money on software, developers, and data scientists. Too often, these AI projects focus on technology at the expense of actionable or tangible business results, resulting in scattershot results and wasted investment. Succeeding with AI sets out a blueprint for AI projects to ensure they are predictable, successful, and profitable. It’s filled with practical techniques for running data science programs that ensure they’re cost effective and focused on the right business goals. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the technology Succeeding with AI requires talent, tools, and money. So why do many well-funded, state-of-the-art projects fail to deliver meaningful business value? Because talent, tools, and money aren’t enough: You also need to know how to ask the right questions. In this unique book, AI consultant Veljko Krunic reveals a tested process to start AI projects right, so you’ll get the results you want. About the book Succeeding with AI sets out a framework for planning and running cost-effective, reliable AI projects that produce real business results. This practical guide reveals secrets forged during the author’s experience with dozens of startups, established businesses, and Fortune 500 giants that will help you establish meaningful, achievable goals. In it you’ll master a repeatable process to maximize the return on data-scientist hours and learn to implement effectiveness metrics for keeping projects on track and resistant to calcification. What's inside Where to invest for maximum payoff How AI projects are different from other software projects Catching early warnings in time to correct course Exercises and examples based on real-world business dilemmas About the reader For project and business leadership, result-focused data scientists, and engineering teams. No AI knowledge required. About the author Veljko Krunic is a data science consultant, has a computer science PhD, and is a certified Six Sigma Master Black Belt. Table of Contents: 1. Introduction 2. How to use AI in your business 3. Choosing your first AI project 4. Linking business and technology 5. What is an ML pipeline, and how does it affect an AI project? 6. Analyzing an ML pipeline 7. Guiding an AI project to success 8. AI trends that may affect you
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Business Intelligence Strategy and Big Data Analytics

More broadly, the goal of this book is to share methods and observations that will help companies achieve BI success and thereby increase revenues, reduce costs, or both.

Author: Steve Williams

Publisher: Morgan Kaufmann

ISBN: 9780128094891

Category: Computers

Page: 240

View: 766

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Business Intelligence Strategy and Big Data Analytics is written for business leaders, managers, and analysts - people who are involved with advancing the use of BI at their companies or who need to better understand what BI is and how it can be used to improve profitability. It is written from a general management perspective, and it draws on observations at 12 companies whose annual revenues range between $500 million and $20 billion. Over the past 15 years, my company has formulated vendor-neutral business-focused BI strategies and program execution plans in collaboration with manufacturers, distributors, retailers, logistics companies, insurers, investment companies, credit unions, and utilities, among others. It is through these experiences that we have validated business-driven BI strategy formulation methods and identified common enterprise BI program execution challenges. In recent years, terms like “big data” and “big data analytics” have been introduced into the business and technical lexicon. Upon close examination, the newer terminology is about the same thing that BI has always been about: analyzing the vast amounts of data that companies generate and/or purchase in the course of business as a means of improving profitability and competitiveness. Accordingly, we will use the terms BI and business intelligence throughout the book, and we will discuss the newer concepts like big data as appropriate. More broadly, the goal of this book is to share methods and observations that will help companies achieve BI success and thereby increase revenues, reduce costs, or both. Provides ideas for improving the business performance of one’s company or business functions Emphasizes proven, practical, step-by-step methods that readers can readily apply in their companies Includes exercises and case studies with road-tested advice about formulating BI strategies and program plans
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