Valuing Data


Valuing Data
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Valuing Data


Valuing Data
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Author : Dewey E. Ray
language : en
Publisher: CRC Press
Release Date : 2018-05-25

Valuing Data written by Dewey E. Ray and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-25 with Computers categories.


The past decade has seen a dramatic increase in the amount and variety of information that is generated and stored electronically by business enterprises. Storing this increased volume of information has not been a problem to date, but as these information stores grow larger and larger, multiple challenges arise for senior management: namely, questions such as "How much is our data worth?" "Are we storing our data in the most cost-effective way?" "Are we managing our data effectively and efficiently?" "Do we know which data is most important?" "Are we extracting business insight from the right data?" "Are our data adding to the value of our business?" "Are our data a liability?" "What is the potential for monetizing our data?" and "Do we have an appropriate risk management plan in place to protect our data?" To answer these value-based questions, data must be treated with the same rigor and discipline as other tangible and intangible assets. In other words, corporate data should be treated as a potential asset and should have its own asset valuation methodology that is accepted by the business community, the accounting and valuation community, and other important stakeholder groups. Valuing Data: An Open Framework is a first step in that direction. Its purpose is to: Provide the reader with some background on the nature of data Present the common categories of business data Explain the importance of data management Report the current thinking on data valuation Offer some business reasons to value data Present an "open framework"—along with some proposed methods—for valuing data The book does not aim to prescribe exactly how data should be valued monetarily, but rather it is a "starting point" for a discussion of data valuation with the objective of developing a stakeholder consensus, which, in turn, will become accepted standards and practices.



The Elements Of Big Data Value


The Elements Of Big Data Value
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Author : Edward Curry
language : en
Publisher: Springer Nature
Release Date : 2021-08-01

The Elements Of Big Data Value written by Edward Curry and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-01 with Computers categories.


This open access book presents the foundations of the Big Data research and innovation ecosystem and the associated enablers that facilitate delivering value from data for business and society. It provides insights into the key elements for research and innovation, technical architectures, business models, skills, and best practices to support the creation of data-driven solutions and organizations. The book is a compilation of selected high-quality chapters covering best practices, technologies, experiences, and practical recommendations on research and innovation for big data. The contributions are grouped into four parts: · Part I: Ecosystem Elements of Big Data Value focuses on establishing the big data value ecosystem using a holistic approach to make it attractive and valuable to all stakeholders. · Part II: Research and Innovation Elements of Big Data Value details the key technical and capability challenges to be addressed for delivering big data value. · Part III: Business, Policy, and Societal Elements of Big Data Value investigates the need to make more efficient use of big data and understanding that data is an asset that has significant potential for the economy and society. · Part IV: Emerging Elements of Big Data Value explores the critical elements to maximizing the future potential of big data value. Overall, readers are provided with insights which can support them in creating data-driven solutions, organizations, and productive data ecosystems. The material represents the results of a collective effort undertaken by the European data community as part of the Big Data Value Public-Private Partnership (PPP) between the European Commission and the Big Data Value Association (BDVA) to boost data-driven digital transformation.



Data Governance


Data Governance
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Author : Neera Bhansali
language : en
Publisher: CRC Press
Release Date : 2013-06-17

Data Governance written by Neera Bhansali and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-06-17 with Computers categories.


As organizations deploy business intelligence and analytic systems to harness business value from their data assets, data governance programs are quickly gaining prominence. And, although data management issues have traditionally been addressed by IT departments, organizational issues critical to successful data management require the implementatio



Big Data For Managers


Big Data For Managers
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Author : Atal Malviya
language : en
Publisher: Routledge
Release Date : 2018-12-07

Big Data For Managers written by Atal Malviya and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-07 with Business & Economics categories.


In today’s fast growing digital world, the web, mobile, social networks and other digital platforms are producing enormous amounts of data that hold intelligence and valuable information. Correctly used it has the power to create sustainable value in different forms for businesses. The commonly used term for this data is Big Data, which includes structured, unstructured and hybrid structured data. However, Big Data is of limited value unless insightful information can be extracted from the sources of data. The solution is Big Data analytics, and how managers and executives can capture value from this vast resource of information and insights. This book develops a simple framework and a non-technical approach to help the reader understand, digest and analyze data, and produce meaningful analytics to make informed decisions. It will support value creation within businesses, from customer care to product innovation, from sales and marketing to operational performance. The authors provide multiple case studies on global industries and business units, chapter summaries and discussion questions for the reader to consider and explore. Big Data for Managers also presents small cases and challenges for the reader to work on – making this a thorough and practical guide for students and managers.



Modern Data Strategy


Modern Data Strategy
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Author : Mike Fleckenstein
language : en
Publisher: Springer
Release Date : 2018-02-12

Modern Data Strategy written by Mike Fleckenstein and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-12 with Computers categories.


This book contains practical steps business users can take to implement data management in a number of ways, including data governance, data architecture, master data management, business intelligence, and others. It defines data strategy, and covers chapters that illustrate how to align a data strategy with the business strategy, a discussion on valuing data as an asset, the evolution of data management, and who should oversee a data strategy. This provides the user with a good understanding of what a data strategy is and its limits. Critical to a data strategy is the incorporation of one or more data management domains. Chapters on key data management domains—data governance, data architecture, master data management and analytics, offer the user a practical approach to data management execution within a data strategy. The intent is to enable the user to identify how execution on one or more data management domains can help solve business issues. This book is intended for business users who work with data, who need to manage one or more aspects of the organization’s data, and who want to foster an integrated approach for how enterprise data is managed. This book is also an excellent reference for students studying computer science and business management or simply for someone who has been tasked with starting or improving existing data management.



Infonomics


Infonomics
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Author : Douglas B. Laney
language : en
Publisher: Routledge
Release Date : 2017-09-05

Infonomics written by Douglas B. Laney and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-05 with Business & Economics categories.


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



Deliver Value In The Data Economy


Deliver Value In The Data Economy
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Author : Jarkko Moilanen
language : en
Publisher: BoD - Books on Demand
Release Date : 2023-02-27

Deliver Value In The Data Economy written by Jarkko Moilanen and has been published by BoD - Books on Demand this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-27 with Business & Economics categories.


The book is for data monetization purposes, helps you to build bridge between IT department and business design to maximise data driven value creation. Data productizement and servitization are explained with real-world example case stories. This book is primarily for data business developers and contains just bare minimum of technical terms.



Value Driven Data


Value Driven Data
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Author : Edosa Odaro
language : en
Publisher: Kogan Page Publishers
Release Date : 2023-08-03

Value Driven Data written by Edosa Odaro and has been published by Kogan Page Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-03 with Business & Economics categories.


Value-Driven Data explains how data and business leaders can co-create and deploy data-driven solutions for their organizations. Value-Driven Data explores how organizations can understand their problems and come up with better solutions, aligning data storytelling with business needs. The book reviews the main challenges that plague most data-to-business interactions and offers actionable strategies for effective data value implementation, including methods for tackling obstacles and incentivizing change. Value-Driven Data is supported by tried-and-tested frameworks that can be applied to different contexts and organizations. It features cutting-edge examples relating to digital transformation, data strategy, resolving conflicts of interests, building a data P&L and AI value prediction methodology. Recognizing different types of data value, this book presents tangible methodologies for identifying, capturing, communicating, measuring and deploying data-enabled opportunities. This is essential reading for data specialists, business stakeholders and leaders involved in capturing and executing data value opportunities for organizations and for informing data value strategies.



Preference Data For Environmental Valuation


Preference Data For Environmental Valuation
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Author : John Whitehead
language : en
Publisher: Routledge
Release Date : 2012-03-15

Preference Data For Environmental Valuation written by John Whitehead and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-03-15 with Business & Economics categories.


The monetary valuation of environmental goods and services has evolved from a fringe field of study in the late 1970s and early 1980s to a primary focus of environmental economists over the past decade. Despite its rapid growth, practitioners of valuation techniques often find themselves defending their practices to both users of the results of applied studies and, perhaps more troubling, to other practitioners. One of the more heated threads of this internal debate over valuation techniques revolves around the types of data to use in performing a valuation study. In the infant years of the development of valuation techniques, two schools of thought emerged: the revealed preference school and the stated preference school, the latter of which is perhaps most associated with the contingent valuation method. In the midst of this debate an exciting new approach to non-market valuation was developed in the 1990s: a combination and joint estimation of revealed preference and stated preference data. There are two primary objectives for this book. One objective is to fill a gap in the nonmarket valuation "primer" literature. A number of books have appeared over the past decade that develop the theory and methods of nonmarket valuation but each takes an individual nonmarket valuation method approach. This book considers each of these valuation methods in combination with another method. These relationships can be exploited econometrically to obtain more valid and reliable estimates of willingness-to-pay relative to the individual methods. The second objective is to showcase recent and novel applications of data combination and joint estimation via a set of original, state-of-the-art studies that are contributed by leading researchers in the field. This book will be accessible to economists and consultants working in business or government, as well as an invaluable resource for researchers and students alike.



Big Data For Twenty First Century Economic Statistics


Big Data For Twenty First Century Economic Statistics
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Author : Katharine G. Abraham
language : en
Publisher: University of Chicago Press
Release Date : 2022-03-11

Big Data For Twenty First Century Economic Statistics written by Katharine G. Abraham and has been published by University of Chicago Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-03-11 with Business & Economics categories.


Introduction.Big data for twenty-first-century economic statistics: the future is now /Katharine G. Abraham, Ron S. Jarmin, Brian C. Moyer, and Matthew D. Shapiro --Toward comprehensive use of big data in economic statistics.Reengineering key national economic indicators /Gabriel Ehrlich, John Haltiwanger, Ron S. Jarmin, David Johnson, and Matthew D. Shapiro ;Big data in the US consumer price index: experiences and plans /Crystal G. Konny, Brendan K. Williams, and David M. Friedman ;Improving retail trade data products using alternative data sources /Rebecca J. Hutchinson ;From transaction data to economic statistics: constructing real-time, high-frequency, geographic measures of consumer spending /Aditya Aladangady, Shifrah Aron-Dine, Wendy Dunn, Laura Feiveson, Paul Lengermann, and Claudia Sahm ;Improving the accuracy of economic measurement with multiple data sources: the case of payroll employment data /Tomaz Cajner, Leland D. Crane, Ryan A. Decker, Adrian Hamins-Puertolas, and Christopher Kurz --Uses of big data for classification.Transforming naturally occurring text data into economic statistics: the case of online job vacancy postings /Arthur Turrell, Bradley Speigner, Jyldyz Djumalieva, David Copple, and James Thurgood ;Automating response evaluation for franchising questions on the 2017 economic census /Joseph Staudt, Yifang Wei, Lisa Singh, Shawn Klimek, J. Bradford Jensen, and Andrew Baer ;Using public data to generate industrial classification codes /John Cuffe, Sudip Bhattacharjee, Ugochukwu Etudo, Justin C. Smith, Nevada Basdeo, Nathaniel Burbank, and Shawn R. Roberts --Uses of big data for sectoral measurement.Nowcasting the local economy: using Yelp data to measure economic activity /Edward L. Glaeser, Hyunjin Kim, and Michael Luca ;Unit values for import and export price indexes: a proof of concept /Don A. Fast and Susan E. Fleck ;Quantifying productivity growth in the delivery of important episodes of care within the Medicare program using insurance claims and administrative data /John A. Romley, Abe Dunn, Dana Goldman, and Neeraj Sood ;Valuing housing services in the era of big data: a user cost approach leveraging Zillow microdata /Marina Gindelsky, Jeremy G. Moulton, and Scott A. Wentland --Methodological challenges and advances.Off to the races: a comparison of machine learning and alternative data for predicting economic indicators /Jeffrey C. Chen, Abe Dunn, Kyle Hood, Alexander Driessen, and Andrea Batch ;A machine learning analysis of seasonal and cyclical sales in weekly scanner data /Rishab Guha and Serena Ng ;Estimating the benefits of new products /W. Erwin Diewert and Robert C. Feenstra.