Search Results: the-data-asset-how-smart-companies-govern-their-data-for-business-success

The Data Asset

How Smart Companies Govern Their Data for Business Success

Author: Tony Fisher

Publisher: John Wiley & Sons

ISBN: 9780470508022

Category: Business & Economics

Page: 240

View: 4334

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

How Smart Companies Govern Their Data for Business Success

Author: Anthony Fisher

Publisher: N.A

ISBN: 9781119204282

Category: Business intelligence

Page: 220

View: 6919

An indispensable guide that shows companies how to treat data as a strategic assetOrganizations 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 Succe.

Big Data, Big Analytics

Emerging Business Intelligence and Analytic Trends for Today's Businesses

Author: Michael Minelli,Michele Chambers,Ambiga Dhiraj

Publisher: John Wiley & Sons

ISBN: 1118239156

Category: Business & Economics

Page: 224

View: 1189

Unique prospective on the big data analytics phenomenon for both business and IT professionals The availability of Big Data, low-cost commodity hardware and new information management and analytics software has produced a unique moment in the history of business. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. These capabilities are neither theoretical nor trivial. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue and profitability. The Age of Big Data is here, and these are truly revolutionary times. This timely book looks at cutting-edge companies supporting an exciting new generation of business analytics. Learn more about the trends in big data and how they are impacting the business world (Risk, Marketing, Healthcare, Financial Services, etc.) Explains this new technology and how companies can use them effectively to gather the data that they need and glean critical insights Explores relevant topics such as data privacy, data visualization, unstructured data, crowd sourcing data scientists, cloud computing for big data, and much more.

Data Strategy

Author: Sid Adelman,Larissa Terpeluk Moss,Majid Abai

Publisher: Addison-Wesley Professional

ISBN: N.A

Category: Computers

Page: 342

View: 7617

Without a data strategy, the people within an organization have no guidelines for making decisions that are absolutely crucial to the success of the IT organization and to the entire organization. The absence of a strategy gives a blank check to those who want to pursue their own agendas, including those who want to try new database management systems, new technologies (often unproven), and new tools. This type of environment provides no hope for success. Data Strategy should result in the development of systems with less risk, higher quality systems, and reusability of assets. This is key to keeping cost and maintenance down, thus running lean and mean. Data Strategy provides a CIO with a rationale to counter arguments for immature technology and data strategies that are inconsistent with existing strategies. This book uses case studies and best practices to give the reader the tools they need to create the best strategy for the organization.

Master Data Management in Practice

Achieving True Customer MDM

Author: Dalton Cervo,Mark Allen

Publisher: John Wiley & Sons

ISBN: 111808568X

Category: Business & Economics

Page: 272

View: 2139

In this book, authors Dalton Cervo and Mark Allen show you how to implement Master Data Management (MDM) within your business model to create a more quality controlled approach. Focusing on techniques that can improve data quality management, lower data maintenance costs, reduce corporate and compliance risks, and drive increased efficiency in customer data management practices, the book will guide you in successfully managing and maintaining your customer master data. You'll find the expert guidance you need, complete with tables, graphs, and charts, in planning, implementing, and managing MDM.

The Data Industry

The Business and Economics of Information and Big Data

Author: Chunlei Tang

Publisher: John Wiley & Sons

ISBN: 111913840X

Category: Mathematics

Page: 216

View: 8873

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

Modern Data Strategy

Author: Mike Fleckenstein,Lorraine Fellows

Publisher: Springer

ISBN: 3319689932

Category: Computers

Page: 263

View: 3771

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.

Exploring Service Science

Author: Gerhard Satzger

Publisher: Springer

ISBN: 3030007138

Category:

Page: N.A

View: 4882

Multi-Domain Master Data Management

Advanced MDM and Data Governance in Practice

Author: Mark Allen,Dalton Cervo

Publisher: Morgan Kaufmann

ISBN: 0128011475

Category: Computers

Page: 244

View: 9530

Multi-Domain Master Data Management delivers practical guidance and specific instruction to help guide planners and practitioners through the challenges of a multi-domain master data management (MDM) implementation. Authors Mark Allen and Dalton Cervo bring their expertise to you in the only reference you need to help your organization take master data management to the next level by incorporating it across multiple domains. Written in a business friendly style with sufficient program planning guidance, this book covers a comprehensive set of topics and advanced strategies centered on the key MDM disciplines of Data Governance, Data Stewardship, Data Quality Management, Metadata Management, and Data Integration. Provides a logical order toward planning, implementation, and ongoing management of multi-domain MDM from a program manager and data steward perspective. Provides detailed guidance, examples and illustrations for MDM practitioners to apply these insights to their strategies, plans, and processes. Covers advanced MDM strategy and instruction aimed at improving data quality management, lowering data maintenance costs, and reducing corporate risks by applying consistent enterprise-wide practices for the management and control of master data.

Bank Fraud

Using Technology to Combat Losses

Author: Revathi Subramanian

Publisher: John Wiley & Sons

ISBN: 1118233972

Category: Business & Economics

Page: 192

View: 1997

Learn how advances in technology can help curb bank fraud Fraud prevention specialists are grappling with ever-mounting quantities of data, but in today's volatile commercial environment, paying attention to that data is more important than ever. Bank Fraud provides a frank discussion of the attitudes, strategies, and—most importantly—the technology that specialists will need to combat fraud. Fraudulent activity may have increased over the years, but so has the field of data science and the results that can be achieved by applying the right principles, a necessary tool today for financial institutions to protect themselves and their clientele. This resource helps professionals in the financial services industry make the most of data intelligence and uncovers the applicable methods to strengthening defenses against fraudulent behavior. This in-depth treatment of the topic begins with a brief history of fraud detection in banking and definitions of key terms, then discusses the benefits of technology, data sharing, and analysis, along with other in-depth information, including: The challenges of fraud detection in a financial services environment The use of statistics, including effective ways to measure losses per account and ROI by product/initiative The Ten Commandments for tackling fraud and ways to build an effective model for fraud management Bank Fraud offers a compelling narrative that ultimately urges security and fraud prevention professionals to make the most of the data they have so painstakingly gathered. Such professionals shouldn't let their most important intellectual asset—data—go to waste. This book shows you just how to leverage data and the most up-to-date tools, technologies, and methods to thwart fraud at every turn.

The Business Forecasting Deal

Exposing Myths, Eliminating Bad Practices, Providing Practical Solutions

Author: Michael Gilliland

Publisher: John Wiley & Sons

ISBN: 9780470769652

Category: Business & Economics

Page: 224

View: 789

Practical-nontechnical-solutions to the problems of business forecasting Written in a nontechnical style, this book provides practical solutions to common business forecasting problems, showing you how to think about business forecasting in the context of uncertainty, randomness and process performance. Addresses the philosophical foundations of forecasting Raises awareness of fundamental issues usually overlooked in pursuit of the perfect forecast Introduces a new way to think about business forecasting, focusing on process efficiency and the elimination of worst practices Provides practical approaches for the non-statistical problems forecasters face Illustrates Forecast Value Added (FVA) Analysis for identifying waste in the forecasting process Couched in the context of uncertainty, randomness, and process performance, this book offers new, innovative ideas for resolving your business forecasting problems.

Infonomics

How to Monetize, Manage, and Measure Information as an Asset for Competitive Advantage

Author: Douglas B. Laney

Publisher: Routledge

ISBN: 1351610694

Category: Business & Economics

Page: 322

View: 7271

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.

Big Data, Data Mining, and Machine Learning

Value Creation for Business Leaders and Practitioners

Author: Jared Dean

Publisher: John Wiley & Sons

ISBN: 1118920708

Category: Computers

Page: 288

View: 1688

With big data analytics comes big insights into profitability Big data is big business. But having the data and the computational power to process it isn't nearly enough to produce meaningful results. Big Data, Data Mining, and Machine Learning: Value Creation for Business Leaders and Practitioners is a complete resource for technology and marketing executives looking to cut through the hype and produce real results that hit the bottom line. Providing an engaging, thorough overview of the current state of big data analytics and the growing trend toward high performance computing architectures, the book is a detail-driven look into how big data analytics can be leveraged to foster positive change and drive efficiency. With continued exponential growth in data and ever more competitive markets, businesses must adapt quickly to gain every competitive advantage available. Big data analytics can serve as the linchpin for initiatives that drive business, but only if the underlying technology and analysis is fully understood and appreciated by engaged stakeholders. This book provides a view into the topic that executives, managers, and practitioners require, and includes: A complete overview of big data and its notable characteristics Details on high performance computing architectures for analytics, massively parallel processing (MPP), and in-memory databases Comprehensive coverage of data mining, text analytics, and machine learning algorithms A discussion of explanatory and predictive modeling, and how they can be applied to decision-making processes Big Data, Data Mining, and Machine Learning provides technology and marketing executives with the complete resource that has been notably absent from the veritable libraries of published books on the topic. Take control of your organization's big data analytics to produce real results with a resource that is comprehensive in scope and light on hyperbole.

Data Driven

Profiting from Your Most Important Business Asset

Author: Thomas C. Redman

Publisher: Harvard Business Press

ISBN: 1422163644

Category: Business & Economics

Page: 257

View: 1638

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.

Total Information Risk Management

Maximizing the Value of Data and Information Assets

Author: Alexander Borek,Ajith Kumar Parlikad,Jela Webb,Philip Woodall

Publisher: Newnes

ISBN: 0124058612

Category: Computers

Page: 316

View: 9830

How well does your organization manage the risks associated with information quality? Managing information risk is becoming a top priority on the organizational agenda. The increasing sophistication of IT capabilities along with the constantly changing dynamics of global competition are forcing businesses to make use of their information more effectively. Information is becoming a core resource and asset for all organizations; however, it also brings many potential risks to an organization, from strategic, operational, financial, compliance, and environmental to societal. If you continue to struggle to understand and measure how information and its quality affects your business, this book is for you. This reference is in direct response to the new challenges that all managers have to face. Our process helps your organization to understand the "pain points" regarding poor data and information quality so you can concentrate on problems that have a high impact on core business objectives. This book provides you with all the fundamental concepts, guidelines and tools to ensure core business information is identified, protected and used effectively, and written in a language that is clear and easy to understand for non-technical managers. Shows how to manage information risk using a holistic approach by examining information from all sources Offers varied perspectives of an author team that brings together academics, practitioners and researchers (both technical and managerial) to provide a comprehensive guide Provides real-life case studies with practical insight into the management of information risk and offers a basis for broader discussion among managers and practitioners

Enterprise Knowledge Management

The Data Quality Approach

Author: David Loshin

Publisher: Morgan Kaufmann

ISBN: 9780124558403

Category: Business & Economics

Page: 493

View: 7034

This volume presents a methodology for defining, measuring and improving data quality. It lays out an economic framework for understanding the value of data quality, then outlines data quality rules and domain- and mapping-based approaches to consolidating enterprise knowledge.

Big Data in Practice

How 45 Successful Companies Used Big Data Analytics to Deliver Extraordinary Results

Author: Bernard Marr

Publisher: John Wiley & Sons

ISBN: 1119231396

Category: Business & Economics

Page: 320

View: 5771

The best-selling author of Big Data is back, this time with a unique and in-depth insight into how specific companies use big data. Big data is on the tip of everyone's tongue. Everyone understands its power and importance, but many fail to grasp the actionable steps and resources required to utilise it effectively. This book fills the knowledge gap by showing how major companies are using big data every day, from an up-close, on-the-ground perspective. From technology, media and retail, to sport teams, government agencies and financial institutions, learn the actual strategies and processes being used to learn about customers, improve manufacturing, spur innovation, improve safety and so much more. Organised for easy dip-in navigation, each chapter follows the same structure to give you the information you need quickly. For each company profiled, learn what data was used, what problem it solved and the processes put it place to make it practical, as well as the technical details, challenges and lessons learned from each unique scenario. Learn how predictive analytics helps Amazon, Target, John Deere and Apple understand their customers Discover how big data is behind the success of Walmart, LinkedIn, Microsoft and more Learn how big data is changing medicine, law enforcement, hospitality, fashion, science and banking Develop your own big data strategy by accessing additional reading materials at the end of each chapter

The Journey Continues: From Data Lake to Data-Driven Organization

Author: Mandy Chessell,Ferd Scheepers,Maryna Strelchuk,Ron van der Starre,Seth Dobrin,Daniel Hernandez,IBM Redbooks

Publisher: IBM Redbooks

ISBN: 0738456667

Category: Computers

Page: 30

View: 9867

This IBM RedguideTM publication looks back on the key decisions that made the data lake successful and looks forward to the future. It proposes that the metadata management and governance approaches developed for the data lake can be adopted more broadly to increase the value that an organization gets from its data. Delivering this broader vision, however, requires a new generation of data catalogs and governance tools built on open standards that are adopted by a multi-vendor ecosystem of data platforms and tools. Work is already underway to define and deliver this capability, and there are multiple ways to engage. This guide covers the reasons why this new capability is critical for modern businesses and how you can get value from it.

The Data and Analytics Playbook

Proven Methods for Governed Data and Analytic Quality

Author: Lowell Fryman,Gregory Lampshire,Dan Meers

Publisher: Morgan Kaufmann

ISBN: 0128025476

Category: Computers

Page: 292

View: 9909

The Data and Analytics Playbook: Proven Methods for Governed Data and Analytic Quality explores the way in which data continues to dominate budgets, along with the varying efforts made across a variety of business enablement projects, including applications, web and mobile computing, big data analytics, and traditional data integration. The book teaches readers how to use proven methods and accelerators to break through data obstacles to provide faster, higher quality delivery of mission critical programs. Drawing upon years of practical experience, and using numerous examples and an easy to understand playbook, Lowell Fryman, Gregory Lampshire, and Dan Meers discuss a simple, proven approach to the execution of multiple data oriented activities. In addition, they present a clear set of methods to provide reliable governance, controls, risk, and exposure management for enterprise data and the programs that rely upon it. In addition, they discuss a cost-effective approach to providing sustainable governance and quality outcomes that enhance project delivery, while also ensuring ongoing controls. Example activities, templates, outputs, resources, and roles are explored, along with different organizational models in common use today and the ways they can be mapped to leverage playbook data governance throughout the organization. Provides a mature and proven playbook approach (methodology) to enabling data governance that supports agile implementation Features specific examples of current industry challenges in enterprise risk management, including anti-money laundering and fraud prevention Describes business benefit measures and funding approaches using exposure based cost models that augment risk models for cost avoidance analysis and accelerated delivery approaches using data integration sprints for application, integration, and information delivery success

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