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The Monetization Of Technical Data
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Book Synopsis The Monetization of Technical Data by : Daniel Trauth
Download or read book The Monetization of Technical Data written by Daniel Trauth and published by Springer Nature. This book was released on 2023-01-01 with total page 659 pages. Available in PDF, EPUB and Kindle. Book excerpt: The monetization of data is a very young topic, for which there are only very few case studies. There is a lack of strategy or concept that shows decision-makers the way into the monetization of data, especially those who have discovered or are threatened by the digital transformation or Industry 4.0. Because machine data is usually unstructured and not usable without domain knowledge/metadata, the monetization of machine data has an as yet unquantifiable potential. In order to make this potential tangible, this work describes not only contributions from science, but also practical examples from industry. Based on different examples from various industries, the reader can already become part of a future data economy today. Values and benefits are described in detail. The translation was done with the help of artificial intelligence. A subsequent human revision was done primarily in terms of content.
Book Synopsis Monetizing Your Data by : Andrew Roman Wells
Download or read book Monetizing Your Data written by Andrew Roman Wells and published by John Wiley & Sons. This book was released on 2017-03-13 with total page 371 pages. Available in PDF, EPUB and Kindle. Book excerpt: Transforming data into revenue generating strategies and actions Organizations are swamped with data—collected from web traffic, point of sale systems, enterprise resource planning systems, and more, but what to do with it? Monetizing your Data provides a framework and path for business managers to convert ever-increasing volumes of data into revenue generating actions through three disciplines: decision architecture, data science, and guided analytics. There are large gaps between understanding a business problem and knowing which data is relevant to the problem and how to leverage that data to drive significant financial performance. Using a proven methodology developed in the field through delivering meaningful solutions to Fortune 500 companies, this book gives you the analytical tools, methods, and techniques to transform data you already have into information into insights that drive winning decisions. Beginning with an explanation of the analytical cycle, this book guides you through the process of developing value generating strategies that can translate into big returns. The companion website, www.monetizingyourdata.com, provides templates, checklists, and examples to help you apply the methodology in your environment, and the expert author team provides authoritative guidance every step of the way. This book shows you how to use your data to: Monetize your data to drive revenue and cut costs Connect your data to decisions that drive action and deliver value Develop analytic tools to guide managers up and down the ladder to better decisions Turning data into action is key; data can be a valuable competitive advantage, but only if you understand how to organize it, structure it, and uncover the actionable information hidden within it through decision architecture and guided analytics. From multinational corporations to single-owner small businesses, companies of every size and structure stand to benefit from these tools, methods, and techniques; Monetizing your Data walks you through the translation and transformation to help you leverage your data into value creating strategies.
Download or read book Infonomics written by Douglas B. Laney and published by Routledge. This book was released on 2017-09-05 with total page 326 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many senior executives talk about information as one of their most important assets, but few behave as if it is. They report to the board on the health of their workforce, their financials, their customers, and their partnerships, but rarely the health of their information assets. Corporations typically exhibit greater discipline in tracking and accounting for their office furniture than their data. Infonomics is the theory, study, and discipline of asserting economic significance to information. It strives to apply both economic and asset management principles and practices to the valuation, handling, and deployment of information assets. This book specifically shows: CEOs and business leaders how to more fully wield information as a corporate asset CIOs how to improve the flow and accessibility of information CFOs how to help their organizations measure the actual and latent value in their information assets. More directly, this book is for the burgeoning force of chief data officers (CDOs) and other information and analytics leaders in their valiant struggle to help their organizations become more infosavvy. Author Douglas Laney has spent years researching and developing Infonomics and advising organizations on the infinite opportunities to monetize, manage, and measure information. This book delivers a set of new ideas, frameworks, evidence, and even approaches adapted from other disciplines on how to administer, wield, and understand the value of information. Infonomics can help organizations not only to better develop, sell, and market their offerings, but to transform their organizations altogether. "Doug Laney masterfully weaves together a collection of great examples with a solid framework to guide readers on how to gain competitive advantage through what he labels "the unruly asset" – data. The framework is comprehensive, the advice practical and the success stories global and across industries and applications." Liz Rowe, Chief Data Officer, State of New Jersey "A must read for anybody who wants to survive in a data centric world." Shaun Adams, Head of Data Science, Betterbathrooms.com "Phenomenal! An absolute must read for data practitioners, business leaders and technology strategists. Doug's lucid style has a set a new standard in providing intelligible material in the field of information economics. His passion and knowledge on the subject exudes thru his literature and inspires individuals like me." Ruchi Rajasekhar, Principal Data Architect, MISO Energy "I highly recommend Infonomics to all aspiring analytics leaders. Doug Laney’s work gives readers a deeper understanding of how and why information should be monetized and managed as an enterprise asset. Laney’s assertion that accounting should recognize information as a capital asset is quite convincing and one I agree with. Infonomics enjoyably echoes that sentiment!" Matt Green, independent business analytics consultant, Atlanta area "If you care about the digital economy, and you should, read this book." Tanya Shuckhart, Analyst Relations Lead, IRI Worldwide
Download or read book Monetizing Data written by Stephan Liozu and published by Ulaga & Associés. This book was released on 2018-10-30 with total page 259 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Digital revolution promises trillions of dollars in created value by 2030. Consultants and researchers are projecting massive and disruptive disruption in entire industrial sectors. As a results, PwC reports in their DigitalIQ report that 73% of executives say that they are investing in internet of things (IoT) and 54% in artificial intelligence. So we are experiencing a deluge of digital investments, programs, and large-scale transformations. Despite this tsunami of activities, many IoT Initiatives stall in the Proof of Concept phase and few are already considered a success. Recently, Siemens revealed that less than a fifth (18%) of surveyed companies analyze more than 60% of production data they collect. In a similar vein, Simon-Kucher & Partners (SKP) reports that 3 out of 4 firms that invested in digitalization in the past 3 years fail in their efforts due to the lack of monetization strategies, the focus on the wrong priorities, the lack of customer intimacy, and the neglect of digital pricing best practices. In fact, only 18% of these firms are true digital heroes. Despite the high level of interest and investments, the reality is that most companies are just getting started. The digital champions are not yet reaping the fruit of their investments. Most companies tend to struggle with the process of designing digital business models, with the development of truly differentiated offers, and with the monetization and pricing of their data-based offers. This book focuses on the topics of data monetization and of the value-based pricing of data-driven offers. The authors introduces a newly-developed practical data monetization roadmap that can be used by digital project teams, incubators, and digital factories to better frame their offers and to apply the principles of value-based pricing. They present options in digital pricing models and practical guidelines on how to deploy them. Readers will learn: The various monetization and value creation models for data-enabled offers The 8 steps of the data monetization framework The best practices in designing differentiated data-enabled offers The value-based pricing of data and options in digital pricing models Business model implications of switching from ownership to consumption model
Book Synopsis Monetizing Innovation by : Madhavan Ramanujam
Download or read book Monetizing Innovation written by Madhavan Ramanujam and published by John Wiley & Sons. This book was released on 2016-05-02 with total page 263 pages. Available in PDF, EPUB and Kindle. Book excerpt: Surprising rules for successful monetization Innovation is the most important driver of growth. Today, more than ever, companies need to innovate to survive. But successful innovation—measured in dollars and cents—is a very hard target to hit. Companies obsess over being creative and innovative and spend significant time and expense in designing and building products, yet struggle to monetize them: 72% of innovations fail to meet their financial targets—or fail entirely. Many companies have come to accept that a high failure rate, and the billions of dollars lost annually, is just the cost of doing business. Monetizing Innovations argues that this is tragic, wasteful, and wrong. Radically improving the odds that your innovation will succeed is just a matter of removing the guesswork. That happens when you put customer demand and willingness to pay in the driver seat—when you design the product around the price. It’s a new paradigm, and that opens the door to true game change: You can stop hoping to monetize, and start knowing that you will. The authors at Simon Kucher know what they’re talking about. As the world’s premier pricing and monetization consulting services company, with 800 professionals in 30 cities around the globe, they have helped clients ranging from massive pharmaceuticals to fast-growing startups find success. In Monetizing Innovation, they distil the lessons of thirty years and over 10,000 projects into a practical, nine-step approach. Whether you are a CEO, executive leadership, or part of the team responsible for innovation and new product development, this book is for you, with special sections and checklist-driven summaries to make monetizing innovation part of your company’s DNA. Illustrative case studies show how some of the world’s best innovative companies like LinkedIn, Uber, Porsche, Optimizely, Draeger, Swarovski and big pharmaceutical companies have used principles outlined in this book. A direct challenge to the status quo “spray and pray” style of innovation, Monetizing Innovation presents a practical approach that can be adopted by any organization, in any industry. Most monetizing innovation failure point home. Now more than ever, companies must rethink the practices that have lost countless billions of dollars. Monetizing Innovation presents a new way forward, and a clear promise: Go from hope to certainty.
Book Synopsis Monetizing Machine Learning by : Manuel Amunategui
Download or read book Monetizing Machine Learning written by Manuel Amunategui and published by Apress. This book was released on 2018-09-12 with total page 510 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take your Python machine learning ideas and create serverless web applications accessible by anyone with an Internet connection. Some of the most popular serverless cloud providers are covered in this book—Amazon, Microsoft, Google, and PythonAnywhere. You will work through a series of common Python data science problems in an increasing order of complexity. The practical projects presented in this book are simple, clear, and can be used as templates to jump-start many other types of projects. You will learn to create a web application around numerical or categorical predictions, understand the analysis of text, create powerful and interactive presentations, serve restricted access to data, and leverage web plugins to accept credit card payments and donations. You will get your projects into the hands of the world in no time. Each chapter follows three steps: modeling the right way, designing and developing a local web application, and deploying onto a popular and reliable serverless cloud provider. You can easily jump to or skip particular topics in the book. You also will have access to Jupyter notebooks and code repositories for complete versions of the code covered in the book. What You’ll Learn Extend your machine learning models using simple techniques to create compelling and interactive web dashboards Leverage the Flask web framework for rapid prototyping of your Python models and ideasCreate dynamic content powered by regression coefficients, logistic regressions, gradient boosting machines, Bayesian classifications, and more Harness the power of TensorFlow by exporting saved models into web applications Create rich web dashboards to handle complex real-time user input with JavaScript and Ajax to yield interactive and tailored contentCreate dashboards with paywalls to offer subscription-based accessAccess API data such as Google Maps, OpenWeather, etc.Apply different approaches to make sense of text data and return customized intelligence Build an intuitive and useful recommendation site to add value to users and entice them to keep coming back Utilize the freemium offerings of Google Analytics and analyze the results Take your ideas all the way to your customer's plate using the top serverless cloud providers Who This Book Is For Those with some programming experience with Python, code editing, and access to an interpreter in working order. The book is geared toward entrepreneurs who want to get their ideas onto the web without breaking the bank, small companies without an IT staff, students wanting exposure and training, and for all data science professionals ready to take things to the next level.
Book Synopsis We Are Data by : John Cheney-Lippold
Download or read book We Are Data written by John Cheney-Lippold and published by NYU Press. This book was released on 2017-05-02 with total page 313 pages. Available in PDF, EPUB and Kindle. Book excerpt: What identity means in an algorithmic age: how it works, how our lives are controlled by it, and how we can resist it Algorithms are everywhere, organizing the near limitless data that exists in our world. Derived from our every search, like, click, and purchase, algorithms determine the news we get, the ads we see, the information accessible to us and even who our friends are. These complex configurations not only form knowledge and social relationships in the digital and physical world, but also determine who we are and who we can be, both on and offline. Algorithms create and recreate us, using our data to assign and reassign our gender, race, sexuality, and citizenship status. They can recognize us as celebrities or mark us as terrorists. In this era of ubiquitous surveillance, contemporary data collection entails more than gathering information about us. Entities like Google, Facebook, and the NSA also decide what that information means, constructing our worlds and the identities we inhabit in the process. We have little control over who we algorithmically are. Our identities are made useful not for us—but for someone else. Through a series of entertaining and engaging examples, John Cheney-Lippold draws on the social constructions of identity to advance a new understanding of our algorithmic identities. We Are Data will educate and inspire readers who want to wrest back some freedom in our increasingly surveilled and algorithmically-constructed world.
Book Synopsis Monetizing Data Management by : Peter Aiken, Juanita Billings
Download or read book Monetizing Data Management written by Peter Aiken, Juanita Billings and published by . This book was released on 2013-10 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: What’s the Return on Investment (ROI) on data management? Sound like an impossible question to answer? Not if you read this book and learn the value-added approach to managing enterprise resources and assets. This book defines the five interrelated best practices that comprise data management, and shows you how by example to successfully communicate data management ROI to senior management. The 17 cases we share will help you to identify opportunities to introduce data management into the strategic conversations that occur in the C-suite. You will gain a new perspective regarding the stewardship of your data assets and insulate your operations from the chaos, losses and risks that result from traditional approaches to technological projects. And you will learn how to protect yourself from legal challenges resulting from outsourced information technology projects gone badly due to incorrect project sequencing and focus. With the emerging acceptance and adoption of revised performance standards, your organization will be better prepared to face the coming big data deluge! The book contains four chapters: • Chapter 1 gives a somewhat unique perspective to the practice of leveraging data. We describe the motivations and delineate the specific challenges preventing most organizations from making substantial progress in this area. • Chapter 2 presents 11 cases where leveraging data has produced positive financial results that can be presented in language of immediate interest to C-level executives. To the degree possible, we have quantified the effect that data management has had in terms that will be meaningful to them also. • Chapter 3 describes five instances taken from the authors' experiences with various governmental defense departments. The lessons in this section however can be equally applied to many non-profit and non-defense governmental organizations. • Chapter 4 speaks specifically to the interaction of data management practices, in terms of both information technology projects and legal responsibilities. Reading it can help your organization avoid a number of perils, stay out of court and better vet contractors, experts and other helpers who play a role in organization information technology development. From John Bottega Foreword: Data is the new currency. Yes, an expression that is being used quite a bit of late, but it is very relevant in discussing the importance of data and the methodologies by which we manage it. And like any currency, how we manage it determines its true value. Like any currency, it can be managed wisely, or it can be managed foolishly. It can be put to good use, or it can be squandered away. The question is – what factors determine the path that we take? How do we properly manage this asset and realize its full value and potential? In Monetizing Data Management, Peter and Juanita explore the question of how to understand and place tangible value on data and data management. They explore this question through a series of examples and real-world use cases to exemplify how the true value of data can be realized. They show how bringing together business and technology, and applying a data-centric forensic approach can turn massive amounts of data into the tools needed to improve business processes, reduce costs, and better serve the customer. Data monetization is not about turning data into money. Instead, it’s about taking information and turning it into opportunity. It’s about the need to understand the real meaning of data in order to extract value from it. And it’s about achieving this objective through a partnership with business and technology. In Monetizing Data Management, the authors demonstrate how true value can be realized from our data through improved data centric approaches.
Book Synopsis Data Monetization by : Gerard Blokdyk
Download or read book Data Monetization written by Gerard Blokdyk and published by Createspace Independent Publishing Platform. This book was released on 2017-10-15 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This powerful Data Monetization self-assessment will make you the dependable Data Monetization domain leader by revealing just what you need to know to be fluent and ready for any Data Monetization challenge. How do I reduce the effort in the Data Monetization work to be done to get problems solved? How can I ensure that plans of action include every Data Monetization task and that every Data Monetization outcome is in place? How will I save time investigating strategic and tactical options and ensuring Data Monetization opportunity costs are low? How can I deliver tailored Data Monetization advise instantly with structured going-forward plans? There's no better guide through these mind-expanding questions than acclaimed best-selling author Gerard Blokdyk. Blokdyk ensures all Data Monetization essentials are covered, from every angle: the Data Monetization self-assessment shows succinctly and clearly that what needs to be clarified to organize the business/project activities and processes so that Data Monetization outcomes are achieved. Contains extensive criteria grounded in past and current successful projects and activities by experienced Data Monetization practitioners. Their mastery, combined with the uncommon elegance of the self-assessment, provides its superior value to you in knowing how to ensure the outcome of any efforts in Data Monetization are maximized with professional results. Your purchase includes access to the $249 value Data Monetization self-assessment dashboard download which gives you your dynamically prioritized projects-ready tool and shows your organization exactly what to do next. Your exclusive instant access details can be found in your book.
Book Synopsis Data Is Everybody's Business by : Barbara H. Wixom
Download or read book Data Is Everybody's Business written by Barbara H. Wixom and published by MIT Press. This book was released on 2023-09-26 with total page 202 pages. Available in PDF, EPUB and Kindle. Book excerpt: A clear, engaging, evidence-based guide to monetizing data, for everyone from employee to board member. Most organizations view data monetization—converting data into money—too narrowly: as merely selling data sets. But data monetization is a core business activity for both commercial and noncommercial organizations, and, within organizations, it’s critical to have wide-ranging support for this pursuit. In Data Is Everybody’s Business, the authors offer a clear and engaging way for people across the entire organization to understand data monetization and make it happen. The authors identify three viable ways to convert data into money—improving work with data, wrapping products with data, and selling information offerings—and explain when to pursue each and how to succeed. Key features of the book: • Grounded in twenty-eight years of academic research, including nine years of research at the MIT Sloan Center for Information Systems Research (MIT CISR) • Definitions of key terms, self-reflection questions, appealing graphics, and easy-to-use frameworks • Rich with detailed case studies • Supplemented by free MIT CISR website resources (cisr.mit.edu) Ideal for organizations engaged in data literacy training, data-driven transformation, or digital transformation, Data Is Everybody’s Business is the essential guide for helping everybody in the organization—not just the data specialists—understand, get excited about, and participate in data monetization.
Book Synopsis Data-Driven Business Models for the Digital Economy by : Rado Kotorov
Download or read book Data-Driven Business Models for the Digital Economy written by Rado Kotorov and published by Business Expert Press. This book was released on 2020-04-21 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: Today the fastest growing companies have no physical assets. Instead, they create innovative digital products and new data-driven business models. They capture huge market share fast and their capitalizations skyrocket. The success of these digital giants is pushing all companies to rethink their business models and to start digitizing their products and services. Whether you are a new start-up building a digital product or service, or an employee of an established company that is transitioning to digital, you need to consider how digitization has transformed every aspect of management. Data-driven business models scale not through asset accumulation and product standardization, but through disaggregation of supply and demand. The winners in the new economy master the demand for one and the supply to millions. Throughout the book the author illustrates with examples and use cases how the market competition has changed and how companies adept to the new rules of the game. The economic levers of scale and scope are also different in the digital economy and companies have to learn new tactics how to achieve and sustain their competitive advantage. While data is at the core of all digital business models, the monetization strategies vary across products, services and business models. Our Monetization Matrix is a model that helps managers, marketers, sales professionals, and technical product designers to align the digital product design with the data-driven business model.
Book Synopsis Computational Advertising by : Peng Liu
Download or read book Computational Advertising written by Peng Liu and published by CRC Press. This book was released on 2020-05-12 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces computational advertising, and Internet monetization. It provides a macroscopic understanding of how consumer products in the Internet era push user experience and monetization to the limit. Part One of the book focuses on the basic problems and background knowledge of online advertising. Part Two targets the product, operations, and sales staff, as well as high-level decision makers of the Internet products. It explains the market structure, trading models, and the main products in computational advertising. Part Three targets systems, algorithms, and architects, and focuses on the key technical challenges of different advertising products. Features · Introduces computational advertising and Internet monetization · Covers data processing, utilization, and trading · Uses business logic as the driving force to explain online advertising products and technology advancement · Explores the products and the technologies of computational advertising, to provide insights on the realization of personalization systems, constrained optimization, data monetization and trading, and other practical industry problems · Includes case studies and code snippets
Download or read book Big Data written by Bill Schmarzo and published by John Wiley & Sons. This book was released on 2013-10-07 with total page 245 pages. Available in PDF, EPUB and Kindle. Book excerpt: Leverage big data to add value to your business Social media analytics, web-tracking, and other technologies help companies acquire and handle massive amounts of data to better understand their customers, products, competition, and markets. Armed with the insights from big data, companies can improve customer experience and products, add value, and increase return on investment. The tricky part for busy IT professionals and executives is how to get this done, and that's where this practical book comes in. Big Data: Understanding How Data Powers Big Business is a complete how-to guide to leveraging big data to drive business value. Full of practical techniques, real-world examples, and hands-on exercises, this book explores the technologies involved, as well as how to find areas of the organization that can take full advantage of big data. Shows how to decompose current business strategies in order to link big data initiatives to the organization’s value creation processes Explores different value creation processes and models Explains issues surrounding operationalizing big data, including organizational structures, education challenges, and new big data-related roles Provides methodology worksheets and exercises so readers can apply techniques Includes real-world examples from a variety of organizations leveraging big data Big Data: Understanding How Data Powers Big Business is written by one of Big Data's preeminent experts, William Schmarzo. Don't miss his invaluable insights and advice.
Book Synopsis The Age of Surveillance Capitalism by : Shoshana Zuboff
Download or read book The Age of Surveillance Capitalism written by Shoshana Zuboff and published by PublicAffairs. This book was released on 2019-01-15 with total page 658 pages. Available in PDF, EPUB and Kindle. Book excerpt: The challenges to humanity posed by the digital future, the first detailed examination of the unprecedented form of power called "surveillance capitalism," and the quest by powerful corporations to predict and control our behavior. In this masterwork of original thinking and research, Shoshana Zuboff provides startling insights into the phenomenon that she has named surveillance capitalism. The stakes could not be higher: a global architecture of behavior modification threatens human nature in the twenty-first century just as industrial capitalism disfigured the natural world in the twentieth. Zuboff vividly brings to life the consequences as surveillance capitalism advances from Silicon Valley into every economic sector. Vast wealth and power are accumulated in ominous new "behavioral futures markets," where predictions about our behavior are bought and sold, and the production of goods and services is subordinated to a new "means of behavioral modification." The threat has shifted from a totalitarian Big Brother state to a ubiquitous digital architecture: a "Big Other" operating in the interests of surveillance capital. Here is the crucible of an unprecedented form of power marked by extreme concentrations of knowledge and free from democratic oversight. Zuboff's comprehensive and moving analysis lays bare the threats to twenty-first century society: a controlled "hive" of total connection that seduces with promises of total certainty for maximum profit -- at the expense of democracy, freedom, and our human future. With little resistance from law or society, surveillance capitalism is on the verge of dominating the social order and shaping the digital future -- if we let it.
Book Synopsis The Economics of Data, Analytics, and Digital Transformation by : Bill Schmarzo
Download or read book The Economics of Data, Analytics, and Digital Transformation written by Bill Schmarzo and published by Packt Publishing Ltd. This book was released on 2020-11-30 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: Build a continuously learning and adapting organization that can extract increasing levels of business, customer and operational value from the amalgamation of data and advanced analytics such as AI and Machine Learning Key Features Master the Big Data Business Model Maturity Index methodology to transition to a value-driven organizational mindset Acquire implementable knowledge on digital transformation through 8 practical laws Explore the economics behind digital assets (data and analytics) that appreciate in value when constructed and deployed correctly Book Description In today's digital era, every organization has data, but just possessing enormous amounts of data is not a sufficient market discriminator. The Economics of Data, Analytics, and Digital Transformation aims to provide actionable insights into the real market discriminators, including an organization's data-fueled analytics products that inspire innovation, deliver insights, help make practical decisions, generate value, and produce mission success for the enterprise. The book begins by first building your mindset to be value-driven and introducing the Big Data Business Model Maturity Index, its maturity index phases, and how to navigate the index. You will explore value engineering, where you will learn how to identify key business initiatives, stakeholders, advanced analytics, data sources, and instrumentation strategies that are essential to data science success. The book will help you accelerate and optimize your company's operations through AI and machine learning. By the end of the book, you will have the tools and techniques to drive your organization's digital transformation. Here are a few words from Dr. Kirk Borne, Data Scientist and Executive Advisor at Booz Allen Hamilton, about the book: "Data analytics should first and foremost be about action and value. Consequently, the great value of this book is that it seeks to be actionable. It offers a dynamic progression of purpose-driven ignition points that you can act upon." What you will learn Train your organization to transition from being data-driven to being value-driven Navigate and master the big data business model maturity index Learn a methodology for determining the economic value of your data and analytics Understand how AI and machine learning can create analytics assets that appreciate in value the more that they are used Become aware of digital transformation misconceptions and pitfalls Create empowered and dynamic teams that fuel your organization's digital transformation Who this book is for This book is designed to benefit everyone from students who aspire to study the economic fundamentals behind data and digital transformation to established business leaders and professionals who want to learn how to leverage data and analytics to accelerate their business careers.
Book Synopsis Work and AI 2030 by : Inka Knappertsbusch
Download or read book Work and AI 2030 written by Inka Knappertsbusch and published by Springer Nature. This book was released on 2023-06-18 with total page 369 pages. Available in PDF, EPUB and Kindle. Book excerpt: In ten years, we will take working with artificial intelligence (AI) more for granted than using cell phones today. 78 recognized experts from practice and research provide deep insights and outlooks regarding the influence of AI on everyday working life in 2030, explaining with practical tips how you can prepare for this development. The 41 concise articles cover a broad spectrum in the area examined in each case. Thanks to a standardized structure, they include a summary of the status quo, concrete examples, future expectations, an overview of challenges and possible solutions, and practical tips. The volume begins with societal and ethical issues before discussing legal considerations for employers and HR professionals, as well as the administration of justice. The other chapters examine the impact of AI on the world of work in 2030 in the sectors of business, industry, mobility and logistics, medicine and pharmaceuticals, and (further) education.
Book Synopsis Data Science For Dummies by : Lillian Pierson
Download or read book Data Science For Dummies written by Lillian Pierson and published by John Wiley & Sons. This book was released on 2021-08-20 with total page 436 pages. Available in PDF, EPUB and Kindle. Book excerpt: Monetize your company’s data and data science expertise without spending a fortune on hiring independent strategy consultants to help What if there was one simple, clear process for ensuring that all your company’s data science projects achieve a high a return on investment? What if you could validate your ideas for future data science projects, and select the one idea that’s most prime for achieving profitability while also moving your company closer to its business vision? There is. Industry-acclaimed data science consultant, Lillian Pierson, shares her proprietary STAR Framework – A simple, proven process for leading profit-forming data science projects. Not sure what data science is yet? Don’t worry! Parts 1 and 2 of Data Science For Dummies will get all the bases covered for you. And if you’re already a data science expert? Then you really won’t want to miss the data science strategy and data monetization gems that are shared in Part 3 onward throughout this book. Data Science For Dummies demonstrates: The only process you’ll ever need to lead profitable data science projects Secret, reverse-engineered data monetization tactics that no one’s talking about The shocking truth about how simple natural language processing can be How to beat the crowd of data professionals by cultivating your own unique blend of data science expertise Whether you’re new to the data science field or already a decade in, you’re sure to learn something new and incredibly valuable from Data Science For Dummies. Discover how to generate massive business wins from your company’s data by picking up your copy today.
