The Data Asset

The Data Asset Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of The Data Asset book. This book definitely worth reading, it is an incredibly well-written.

The Data Asset

Tony Fisher
The Data Asset Book PDF

Author : Tony Fisher
Publisher : John Wiley & Sons
Page : 246 pages
File Size : 53,9 Mb
Release : 2009-06-22
Category : Business & Economics
ISBN : 9780470462263

Get Book

The Data Asset by Tony Fisher Pdf

An indispensable guide that shows companies how to treat data as a strategic asset Organizations set their business strategy and direction based on information that is available to executives. The Data Asset provides guidance for not only building the business case for data quality and data governance, but also for developing methodologies and processes that will enable your organization to better treat its data as a strategic asset. Part of Wiley's SAS Business Series, this book looks at Business Case Building; Maturity Model and Organization Capabilities; 7-Step Programmatic Approach for Success; and Technologies Required for Effective Data Quality and Data Governance and, within these areas, covers Risk mitigation Cost control Revenue optimization Undisciplined and reactive organizations Proactive organizations Analysis, improvement, and control technology Whether you're a business manager or an IT professional, The Data Asset reveals the methodology and technology needed to approach successful data quality and data governance initiatives on an enterprise scale.

The Data Asset

Tony Fisher
The Data Asset Book PDF

Author : Tony Fisher
Publisher : John Wiley & Sons
Page : 246 pages
File Size : 52,7 Mb
Release : 2009-06-22
Category : Business & Economics
ISBN : 9780470508022

Get Book

The Data Asset by Tony Fisher Pdf

An indispensable guide that shows companies how to treat data as a strategic asset Organizations set their business strategy and direction based on information that is available to executives. The Data Asset provides guidance for not only building the business case for data quality and data governance, but also for developing methodologies and processes that will enable your organization to better treat its data as a strategic asset. Part of Wiley's SAS Business Series, this book looks at Business Case Building; Maturity Model and Organization Capabilities; 7-Step Programmatic Approach for Success; and Technologies Required for Effective Data Quality and Data Governance and, within these areas, covers Risk mitigation Cost control Revenue optimization Undisciplined and reactive organizations Proactive organizations Analysis, improvement, and control technology Whether you're a business manager or an IT professional, The Data Asset reveals the methodology and technology needed to approach successful data quality and data governance initiatives on an enterprise scale.

Practical Cloud Security

Chris Dotson
Practical Cloud Security Book PDF

Author : Chris Dotson
Publisher : O'Reilly Media
Page : 195 pages
File Size : 42,8 Mb
Release : 2019-03-04
Category : Computers
ISBN : 9781492037484

Get Book

Practical Cloud Security by Chris Dotson Pdf

With their rapidly changing architecture and API-driven automation, cloud platforms come with unique security challenges and opportunities. This hands-on book guides you through security best practices for multivendor cloud environments, whether your company plans to move legacy on-premises projects to the cloud or build a new infrastructure from the ground up. Developers, IT architects, and security professionals will learn cloud-specific techniques for securing popular cloud platforms such as Amazon Web Services, Microsoft Azure, and IBM Cloud. Chris Dotson—an IBM senior technical staff member—shows you how to establish data asset management, identity and access management, vulnerability management, network security, and incident response in your cloud environment.

Data Driven

Thomas C. Redman
Data Driven Book PDF

Author : Thomas C. Redman
Publisher : Harvard Business Press
Page : 257 pages
File Size : 49,5 Mb
Release : 2008-09-22
Category : Business & Economics
ISBN : 9781422163641

Get Book

Data Driven by Thomas C. Redman Pdf

Your company's data has the potential to add enormous value to every facet of the organization -- from marketing and new product development to strategy to financial management. Yet if your company is like most, it's not using its data to create strategic advantage. Data sits around unused -- or incorrect data fouls up operations and decision making. In Data Driven, Thomas Redman, the "Data Doc," shows how to leverage and deploy data to sharpen your company's competitive edge and enhance its profitability. The author reveals: · The special properties that make data such a powerful asset · The hidden costs of flawed, outdated, or otherwise poor-quality data · How to improve data quality for competitive advantage · Strategies for exploiting your data to make better business decisions · The many ways to bring data to market · Ideas for dealing with political struggles over data and concerns about privacy rights Your company's data is a key business asset, and you need to manage it aggressively and professionally. Whether you're a top executive, an aspiring leader, or a product-line manager, this eye-opening book provides the tools and thinking you need to do that.

Infonomics

Douglas B. Laney
Infonomics Book PDF

Author : Douglas B. Laney
Publisher : Routledge
Page : 326 pages
File Size : 48,9 Mb
Release : 2017-09-05
Category : Business & Economics
ISBN : 9781351610698

Get Book

Infonomics by Douglas B. Laney Pdf

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

Assetization

Kean Birch,Fabian Muniesa
Assetization Book PDF

Author : Kean Birch,Fabian Muniesa
Publisher : MIT Press
Page : 339 pages
File Size : 48,9 Mb
Release : 2020-07-14
Category : Business & Economics
ISBN : 9780262539173

Get Book

Assetization by Kean Birch,Fabian Muniesa Pdf

How the asset—anything that can be controlled, traded, and capitalized as a revenue stream—has become the primary basis of technoscientific capitalism. In this book, scholars from a range of disciplines argue that the asset—meaning anything that can be controlled, traded, and capitalized as a revenue stream—has become the primary basis of technoscientific capitalism. An asset can be an object or an experience, a sum of money or a life form, a patent or a bodily function. A process of assetization prevails, imposing investment and return as the key rationale, and overtaking commodification and its speculative logic. Although assets can be bought and sold, the point is to get a durable economic rent from them rather than make a killing on the market. Assetization examines how assets are constructed and how a variety of things can be turned into assets, analyzing the interests, activities, skills, organizations, and relations entangled in this process. The contributors consider the assetization of knowledge, including patents, personal data, and biomedical innovation; of infrastructure, including railways and energy; of nature, including mineral deposits, agricultural seeds, and “natural capital”; and of publics, including such public goods as higher education and “monetizable social ills.” Taken together, the chapters show the usefulness of assetization as an analytical tool and as an element in the critique of capitalism. Contributors Thomas Beauvisage, Kean Birch, Veit Braun, Natalia Buier, Béatrice Cointe, Paul Robert Gilbert, Hyo Yoon Kang, Les Levidow, Kevin Mellet, Sveta Milyaeva, Fabian Muniesa, Alain Nadaï, Daniel Neyland, Victor Roy, James W. Williams

Machine Learning for Asset Managers

Marcos M. López de Prado
Machine Learning for Asset Managers Book PDF

Author : Marcos M. López de Prado
Publisher : Cambridge University Press
Page : 152 pages
File Size : 45,8 Mb
Release : 2020-04-22
Category : Business & Economics
ISBN : 9781108879729

Get Book

Machine Learning for Asset Managers by Marcos M. López de Prado Pdf

Successful investment strategies are specific implementations of general theories. An investment strategy that lacks a theoretical justification is likely to be false. Hence, an asset manager should concentrate her efforts on developing a theory rather than on backtesting potential trading rules. The purpose of this Element is to introduce machine learning (ML) tools that can help asset managers discover economic and financial theories. ML is not a black box, and it does not necessarily overfit. ML tools complement rather than replace the classical statistical methods. Some of ML's strengths include (1) a focus on out-of-sample predictability over variance adjudication; (2) the use of computational methods to avoid relying on (potentially unrealistic) assumptions; (3) the ability to "learn" complex specifications, including nonlinear, hierarchical, and noncontinuous interaction effects in a high-dimensional space; and (4) the ability to disentangle the variable search from the specification search, robust to multicollinearity and other substitution effects.

Data Intensive Industrial Asset Management

Farhad Balali,Jessie Nouri,Adel Nasiri,Tian Zhao
Data Intensive Industrial Asset Management Book PDF

Author : Farhad Balali,Jessie Nouri,Adel Nasiri,Tian Zhao
Publisher : Springer Nature
Page : 247 pages
File Size : 49,8 Mb
Release : 2020-01-22
Category : Technology & Engineering
ISBN : 9783030359300

Get Book

Data Intensive Industrial Asset Management by Farhad Balali,Jessie Nouri,Adel Nasiri,Tian Zhao Pdf

This book presents a step by step Asset Health Management Optimization Approach Using Internet of Things (IoT). The authors provide a comprehensive study which includes the descriptive, diagnostic, predictive, and prescriptive analysis in detail. The presentation focuses on the challenges of the parameter selection, statistical data analysis, predictive algorithms, big data storage and selection, data pattern recognition, machine learning techniques, asset failure distribution estimation, reliability and availability enhancement, condition based maintenance policy, failure detection, data driven optimization algorithm, and a multi-objective optimization approach, all of which can significantly enhance the reliability and availability of the system.

Artificial Intelligence in Asset Management

Söhnke M. Bartram,Jürgen Branke,Mehrshad Motahari
Artificial Intelligence in Asset Management Book PDF

Author : Söhnke M. Bartram,Jürgen Branke,Mehrshad Motahari
Publisher : CFA Institute Research Foundation
Page : 95 pages
File Size : 40,5 Mb
Release : 2020-08-28
Category : Business & Economics
ISBN : 9781952927034

Get Book

Artificial Intelligence in Asset Management by Söhnke M. Bartram,Jürgen Branke,Mehrshad Motahari Pdf

Artificial intelligence (AI) has grown in presence in asset management and has revolutionized the sector in many ways. It has improved portfolio management, trading, and risk management practices by increasing efficiency, accuracy, and compliance. In particular, AI techniques help construct portfolios based on more accurate risk and return forecasts and more complex constraints. Trading algorithms use AI to devise novel trading signals and execute trades with lower transaction costs. AI also improves risk modeling and forecasting by generating insights from new data sources. Finally, robo-advisors owe a large part of their success to AI techniques. Yet the use of AI can also create new risks and challenges, such as those resulting from model opacity, complexity, and reliance on data integrity.

Street Data

Shane Safir,Jamila Dugan
Street Data Book PDF

Author : Shane Safir,Jamila Dugan
Publisher : Corwin
Page : 281 pages
File Size : 53,8 Mb
Release : 2021-02-12
Category : Education
ISBN : 9781071812662

Get Book

Street Data by Shane Safir,Jamila Dugan Pdf

Radically reimagine our ways of being, learning, and doing Education can be transformed if we eradicate our fixation on big data like standardized test scores as the supreme measure of equity and learning. Instead of the focus being on "fixing" and "filling" academic gaps, we must envision and rebuild the system from the student up—with classrooms, schools and systems built around students’ brilliance, cultural wealth, and intellectual potential. Street data reminds us that what is measurable is not the same as what is valuable and that data can be humanizing, liberatory and healing. By breaking down street data fundamentals: what it is, how to gather it, and how it can complement other forms of data to guide a school or district’s equity journey, Safir and Dugan offer an actionable framework for school transformation. Written for educators and policymakers, this book · Offers fresh ideas and innovative tools to apply immediately · Provides an asset-based model to help educators look for what’s right in our students and communities instead of seeking what’s wrong · Explores a different application of data, from its capacity to help us diagnose root causes of inequity, to its potential to transform learning, and its power to reshape adult culture Now is the time to take an antiracist stance, interrogate our assumptions about knowledge, measurement, and what really matters when it comes to educating young people.

Machine Learning in Asset Pricing

Stefan Nagel
Machine Learning in Asset Pricing Book PDF

Author : Stefan Nagel
Publisher : Princeton University Press
Page : 156 pages
File Size : 42,9 Mb
Release : 2021-05-11
Category : Business & Economics
ISBN : 9780691218700

Get Book

Machine Learning in Asset Pricing by Stefan Nagel Pdf

A groundbreaking, authoritative introduction to how machine learning can be applied to asset pricing Investors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such data-rich, high-dimensional environments, techniques from the rapidly advancing field of machine learning (ML) are well-suited for solving prediction problems. Accordingly, ML methods are quickly becoming part of the toolkit in asset pricing research and quantitative investing. In this book, Stefan Nagel examines the promises and challenges of ML applications in asset pricing. Asset pricing problems are substantially different from the settings for which ML tools were developed originally. To realize the potential of ML methods, they must be adapted for the specific conditions in asset pricing applications. Economic considerations, such as portfolio optimization, absence of near arbitrage, and investor learning can guide the selection and modification of ML tools. Beginning with a brief survey of basic supervised ML methods, Nagel then discusses the application of these techniques in empirical research in asset pricing and shows how they promise to advance the theoretical modeling of financial markets. Machine Learning in Asset Pricing presents the exciting possibilities of using cutting-edge methods in research on financial asset valuation.

Data Science for Business

Foster Provost,Tom Fawcett
Data Science for Business Book PDF

Author : Foster Provost,Tom Fawcett
Publisher : "O'Reilly Media, Inc."
Page : 414 pages
File Size : 49,7 Mb
Release : 2013-07-27
Category : Computers
ISBN : 9781449374280

Get Book

Data Science for Business by Foster Provost,Tom Fawcett Pdf

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

Leading Digital

George Westerman,Didier Bonnet,Andrew McAfee
Leading Digital Book PDF

Author : George Westerman,Didier Bonnet,Andrew McAfee
Publisher : Harvard Business Review Press
Page : 303 pages
File Size : 40,9 Mb
Release : 2014-09-23
Category : Business & Economics
ISBN : 9781625272485

Get Book

Leading Digital by George Westerman,Didier Bonnet,Andrew McAfee Pdf

Become a Digital Master—No Matter What Business You’re In If you think the phrase “going digital” is only relevant for industries like tech, media, and entertainment—think again. In fact, mobile, analytics, social media, sensors, and cloud computing have already fundamentally changed the entire business landscape as we know it—including your industry. The problem is that most accounts of digital in business focus on Silicon Valley stars and tech start-ups. But what about the other 90-plus percent of the economy? In Leading Digital, authors George Westerman, Didier Bonnet, and Andrew McAfee highlight how large companies in traditional industries—from finance to manufacturing to pharmaceuticals—are using digital to gain strategic advantage. They illuminate the principles and practices that lead to successful digital transformation. Based on a study of more than four hundred global firms, including Asian Paints, Burberry, Caesars Entertainment, Codelco, Lloyds Banking Group, Nike, and Pernod Ricard, the book shows what it takes to become a Digital Master. It explains successful transformation in a clear, two-part framework: where to invest in digital capabilities, and how to lead the transformation. Within these parts, you’ll learn: • How to engage better with your customers • How to digitally enhance operations • How to create a digital vision • How to govern your digital activities The book also includes an extensive step-by-step transformation playbook for leaders to follow. Leading Digital is the must-have guide to help your organization survive and thrive in the new, digitally powered, global economy.

The Case for the Chief Data Officer

Peter Aiken,Michael M. Gorman
The Case for the Chief Data Officer Book PDF

Author : Peter Aiken,Michael M. Gorman
Publisher : Newnes
Page : 89 pages
File Size : 54,6 Mb
Release : 2013-04-22
Category : Computers
ISBN : 9780124114951

Get Book

The Case for the Chief Data Officer by Peter Aiken,Michael M. Gorman Pdf

Data are an organization's sole, non-depletable, non-degrading, durable asset. Engineered right, data's value increases over time because the added dimensions of time, geography, and precision. To achieve data's full organizational value, there must be dedicated individual to leverage data as assets - a Chief Data Officer or CDO who's three job pillars are: Dedication solely to leveraging data assets, Unconstrained by an IT project mindset, and Reports directly to the business Once these three pillars are set into place, organizations can leverage their data assets. Data possesses properties worthy of additional investment. Many existing CDOs are fatally crippled, however, because they lack one or more of these three pillars. Often organizations have some or all pillars already in place but are not operating in a coordinated manner. The overall objective of this book is to present these pillars in an understandable way, why each is necessary (but insufficient), and what do to about it. Uncovers that almost all organizations need sophisticated, comprehensive data management education and strategies. Delivery of organization-wide data success requires a highly focused, full time Chief Data Officer. Engineers organization-wide data advantage which enables success in the marketplace

DAMA-DMBOK

Dama International
DAMA DMBOK Book PDF

Author : Dama International
Publisher : Unknown
Page : 628 pages
File Size : 50,7 Mb
Release : 2017
Category : Database management
ISBN : 1634622340

Get Book

DAMA-DMBOK by Dama International Pdf

Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment.