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data governance risk management: Data Protection David G. Hill, 2016-04-19 Failure to appreciate the full dimensions of data protection can lead to poor data protection management, costly resource allocation issues, and exposure to unnecessary risks. Data Protection: Governance, Risk Management, and Compliance explains how to gain a handle on the vital aspects of data protection.The author begins by building the foundatio |
data governance risk management: Non-Invasive Data Governance Robert S. Seiner, 2014-09-01 Data-governance programs focus on authority and accountability for the management of data as a valued organizational asset. Data Governance should not be about command-and-control, yet at times could become invasive or threatening to the work, people and culture of an organization. Non-Invasive Data Governance™ focuses on formalizing existing accountability for the management of data and improving formal communications, protection, and quality efforts through effective stewarding of data resources. Non-Invasive Data Governance will provide you with a complete set of tools to help you deliver a successful data governance program. Learn how: • Steward responsibilities can be identified and recognized, formalized, and engaged according to their existing responsibility rather than being assigned or handed to people as more work. • Governance of information can be applied to existing policies, standard operating procedures, practices, and methodologies, rather than being introduced or emphasized as new processes or methods. • Governance of information can support all data integration, risk management, business intelligence and master data management activities rather than imposing inconsistent rigor to these initiatives. • A practical and non-threatening approach can be applied to governing information and promoting stewardship of data as a cross-organization asset. • Best practices and key concepts of this non-threatening approach can be communicated effectively to leverage strengths and address opportunities to improve. |
data governance risk management: Data Governance: The Definitive Guide Evren Eryurek, Uri Gilad, Valliappa Lakshmanan, Anita Kibunguchy-Grant, Jessi Ashdown, 2021-03-08 As your company moves data to the cloud, you need to consider a comprehensive approach to data governance, along with well-defined and agreed-upon policies to ensure you meet compliance. Data governance incorporates the ways that people, processes, and technology work together to support business efficiency. With this practical guide, chief information, data, and security officers will learn how to effectively implement and scale data governance throughout their organizations. You'll explore how to create a strategy and tooling to support the democratization of data and governance principles. Through good data governance, you can inspire customer trust, enable your organization to extract more value from data, and generate more-competitive offerings and improvements in customer experience. This book shows you how. Enable auditable legal and regulatory compliance with defined and agreed-upon data policies Employ better risk management Establish control and maintain visibility into your company's data assets, providing a competitive advantage Drive top-line revenue and cost savings when developing new products and services Implement your organization's people, processes, and tools to operationalize data trustworthiness. |
data governance risk management: The DAMA Dictionary of Data Management Dama International, 2011 A glossary of over 2,000 terms which provides a common data management vocabulary for IT and Business professionals, and is a companion to the DAMA Data Management Body of Knowledge (DAMA-DMBOK). Topics include: Analytics & Data Mining Architecture Artificial Intelligence Business Analysis DAMA & Professional Development Databases & Database Design Database Administration Data Governance & Stewardship Data Management Data Modeling Data Movement & Integration Data Quality Management Data Security Management Data Warehousing & Business Intelligence Document, Record & Content Management Finance & Accounting Geospatial Data Knowledge Management Marketing & Customer Relationship Management Meta-Data Management Multi-dimensional & OLAP Normalization Object-Orientation Parallel Database Processing Planning Process Management Project Management Reference & Master Data Management Semantic Modeling Software Development Standards Organizations Structured Query Language (SQL) XML Development |
data governance risk management: Data Governance and Compliance Rupa Mahanti, 2021-04-27 This book sets the stage of the evolution of corporate governance, laws and regulations, other forms of governance, and the interaction between data governance and other corporate governance sub-disciplines. Given the continuously evolving and complex regulatory landscape and the growing number of laws and regulations, compliance is a widely discussed issue in the field of data. This book considers the cost of non-compliance bringing in examples from different industries of instances in which companies failed to comply with rules, regulations, and other legal obligations, and goes on to explain how data governance helps in avoiding such pitfalls. The first in a three-volume series on data governance, this book does not assume any prior or specialist knowledge in data governance and will be highly beneficial for IT, management and law students, academics, information management and business professionals, and researchers to enhance their knowledge and get guidance in managing their own data governance projects from a governance and compliance perspective. |
data governance risk management: The Data Governance Imperative Steve Sarsfield, 2009-04-23 This practical book covers both strategies and tactics around managing a data governance initiative to help make the most of your data. |
data governance risk management: Decision and Game Theory for Security Jens Grossklags, Jean Walrand, 2012-09-27 This book constitutes the refereed proceedings of the Third International Conference on Decision and Game Theory for Security, GameSec 2012, held in Budapest, Hungary, in November 2012. The 18 revised full papers presented were carefully reviewed and selected from numerous submissions. The papers are organized in topical sections on secret communications, identification of attackers, multi-step attacks, network security, system defense, and applications security. |
data governance risk management: Governance, Risk Management, and Compliance Richard M. Steinberg, 2011-08-02 An expert's insider secrets to how successful CEOs and directors shape, lead, and oversee their organizations to achieve corporate goals Governance, Risk Management, and Compliance shows senior executives and board members how to ensure that their companies incorporate the necessary processes, organization, and technology to accomplish strategic goals. Examining how and why some major companies failed while others continue to grow and prosper, author and internationally recognized expert Richard Steinberg reveals how to cultivate a culture, leadership process and infrastructure toward achieving business objectives and related growth, profit, and return goals. Explains critical factors that make compliance and ethics programs and risk management processes really work Explores the board's role in overseeing corporate strategy, risk management, CEO compensation, succession planning, crisis planning, performance measures, board composition, and shareholder communications Highlights for CEOs, senior management teams, and board members the pitfalls to avoid and what must go right for success Outlines the future of corporate governance and what's needed for continued effectiveness Written by well-known corporate governance and risk management expert Richard Steinberg Governance, Risk Management, and Compliance lays a sound foundation and provides critical insights for understanding the role of governance, risk management, and compliance and its successful implementation in today's business environment. |
data governance risk management: Financial Analysis and Risk Management Victoria Lemieux, 2012-10-20 The Global Financial Crisis and the Eurozone crisis that has followed have drawn attention to weaknesses in financial records, information and data. These weaknesses have led to operational risks in financial institutions, flawed bankruptcy and foreclosure proceedings following the Crisis, and inadequacies in financial supervisors’ access to records and information for the purposes of a prudential response. Research is needed to identify the practices that will provide the records, information and data needed to support more effective financial analysis and risk management. The unique contribution of this volume is in bringing together researchers in distinct domains that seldom interact to identify theoretical, technological, policy and practical issues related to the management of financial records, information and data. The book will, therefore, appeal to researchers or advanced practitioners in the field of finance and those with an interest in risk management, computer science, cognitive science, sociology, management information systems, information science, and archival science as applied to the financial domain. |
data governance risk management: Data Governance John Ladley, 2019-11-08 Managing data continues to grow as a necessity for modern organizations. There are seemingly infinite opportunities for organic growth, reduction of costs, and creation of new products and services. It has become apparent that none of these opportunities can happen smoothly without data governance. The cost of exponential data growth and privacy / security concerns are becoming burdensome. Organizations will encounter unexpected consequences in new sources of risk. The solution to these challenges is also data governance; ensuring balance between risk and opportunity. Data Governance, Second Edition, is for any executive, manager or data professional who needs to understand or implement a data governance program. It is required to ensure consistent, accurate and reliable data across their organization. This book offers an overview of why data governance is needed, how to design, initiate, and execute a program and how to keep the program sustainable. This valuable resource provides comprehensive guidance to beginning professionals, managers or analysts looking to improve their processes, and advanced students in Data Management and related courses. With the provided framework and case studies all professionals in the data governance field will gain key insights into launching successful and money-saving data governance program. - Incorporates industry changes, lessons learned and new approaches - Explores various ways in which data analysts and managers can ensure consistent, accurate and reliable data across their organizations - Includes new case studies which detail real-world situations - Explores all of the capabilities an organization must adopt to become data driven - Provides guidance on various approaches to data governance, to determine whether an organization should be low profile, central controlled, agile, or traditional - Provides guidance on using technology and separating vendor hype from sincere delivery of necessary capabilities - Offers readers insights into how their organizations can improve the value of their data, through data quality, data strategy and data literacy - Provides up to 75% brand-new content compared to the first edition |
data governance risk management: Total Information Risk Management Alexander Borek, Ajith Kumar Parlikad, Jela Webb, Philip Woodall, 2013-08-30 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 |
data governance risk management: Data Governance Neera Bhansali, 2013-06-17 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 |
data governance risk management: Risk Management and Governance Terje Aven, Ortwin Renn, 2010-09-27 Risk is a popular topic in many sciences - in natural, medical, statistical, engineering, social, economic and legal disciplines. Yet, no single discipline can grasp the full meaning of risk. Investigating risk requires a multidisciplinary approach. The authors, coming from two very different disciplinary traditions, meet this challenge by building bridges between the engineering, the statistical and the social science perspectives. The book provides a comprehensive, accessible and concise guide to risk assessment, management and governance. A basic pillar for the book is the risk governance framework proposed by the International Risk Governance Council (IRGC). This framework offers a comprehensive means of integrating risk identification, assessment, management and communication. The authors develop and explain new insights and add substance to the various elements of the framework. The theoretical analysis is illustrated by several examples from different areas of applications. |
data governance risk management: Securing an IT Organization through Governance, Risk Management, and Audit Ken E. Sigler, James L. Rainey III, 2016-01-05 This book introduces two internationally recognized bodies of knowledge: COBIT 5 from a cybersecurity perspective and the NIST Framework for Improving Critical Infrastructure Cybersecurity (CSF). Emphasizing the processes directly related to governance, risk management, and audit, the book maps the CSF steps and activities to the methods defined in COBIT 5, extending the CSF objectives with practical and measurable activities that leverage operational risk understanding in a business context. This allows the ICT organization to convert high-level enterprise goals into manageable, specific goals rather than unintegrated checklist models. |
data governance risk management: OECD Health Policy Studies Health Data Governance Privacy, Monitoring and Research OECD, 2015-10-05 This report identifies eight key data governance mechanisms to maximise benefits to patients and to societies from the collection, linkage and analysis of health data, and to minimise risks to both patient privacy and the security of health data. |
data governance risk management: Data Risk Management: Essentials to implement an Enterprise Control Environment Tejasvi Addagada , 2022-07-08 About the book (in English for listing the book on online portals in 100-150 words): You must hear this often if you manage any kind of risk - risk and value go together. And that's true, of course for data! Both data and its infrastructure must be managed for their benefits and risks. The purpose of the book is to elaborate on this need to formalize data risk management. Today, regulations drive enterprises to assess data related risks. Prioritizing and managing data associated with financial or operational risk has been the corner-stone of most regulations like BCBS, CCAR, GDPR to name a few. Nevertheless, data risks can extend beyond regulations to improve existing control environments in companies. By doing so, we will maximize the potential of data capabilities to reach 100%. Through structural alignment within the board and formalizing a data-risk function, the book focuses on managing data risks. Furthermore, the book explains quantitative and qualitative approaches to data risk assessments along with popular tools and techniques. Also, Tejasvi discusses a proven approach to managing data risks called capability-based assessment. As a technique, this can also be applied to data risk planning and formulating a data risk strategy. Twenty data risks and privacy risks are provided in this book by way of examples. These are accompanied by details such as a risk statements, scenarios, causes, and categories of impact if the data risks are to manifest |
data governance risk management: Data Management and Governance Services Tejasvi Addagada, 2017-06-22 Organizations across industries are embracing data management and governance practices, primarily driven by regulation and service excellence. While it is equally important to set up a data office, it is also crucial to ensure sustainability of the function. Also, data governance is a pervasive enabler that supports a firm's corporate governance principles. The book highlights how an Enterprise can: -Overcome challenges in data offices today -Analyze existing data management strategy and capabilities to traverse maturity -Set up metadata and data quality management as services and successfully operationalize them -Formalize governance as a function through an operating model, based on its enabling culture -Define a benefits realization model to assess and monitor the value of managing and governing data |
data governance risk management: Data Goverence for the Executive, Orr James C., 2011-01-01 |
data governance risk management: Information Governance Robert F. Smallwood, 2014-03-28 Proven and emerging strategies for addressing document and records management risk within the framework of information governance principles and best practices Information Governance (IG) is a rapidly emerging super discipline and is now being applied to electronic document and records management, email, social media, cloud computing, mobile computing, and, in fact, the management and output of information organization-wide. IG leverages information technologies to enforce policies, procedures and controls to manage information risk in compliance with legal and litigation demands, external regulatory requirements, and internal governance objectives. Information Governance: Concepts, Strategies, and Best Practices reveals how, and why, to utilize IG and leverage information technologies to control, monitor, and enforce information access and security policies. Written by one of the most recognized and published experts on information governance, including specialization in e-document security and electronic records management Provides big picture guidance on the imperative for information governance and best practice guidance on electronic document and records management Crucial advice and insights for compliance and risk managers, operations managers, corporate counsel, corporate records managers, legal administrators, information technology managers, archivists, knowledge managers, and information governance professionals IG sets the policies that control and manage the use of organizational information, including social media, mobile computing, cloud computing, email, instant messaging, and the use of e-documents and records. This extends to e-discovery planning and preparation. Information Governance: Concepts, Strategies, and Best Practices provides step-by-step guidance for developing information governance strategies and practices to manage risk in the use of electronic business documents and records. |
data governance risk management: COSO Enterprise Risk Management Robert R. Moeller, 2007-07-20 Praise for COSO Enterprise Risk Management COSO ERM is a thoughtful introduction to the challenges of risk management at the enterprise level and contains a wealth of information on dealing with it through the use of the COSO framework. Detailed procedures covering a wide variety of situations are followed by a thorough explanation of how each is deployed. As a project management professional, I appreciate how the author addresses the need for risk management at a project level. His background as someone who 'practices what they preach' and realizes the impact of the Sarbanes-Oxley auditing rules comes through clearly in the book, and it should be mandatory reading for anyone seeking to understand how to tackle their own ERM issues. --Greg Gomel, PMP, CQM, CSQE, ITIL, Director, Project Management, Insight North America This volume clearly and comprehensively outlines the usefulness of COSO Enterprise Risk Management guidance. It should provide considerable benefit to those having governance responsibilities in this important area. --Curtis Verschoor, L & Q Research Professor, School of Accountancy and MISDePaul University, Chicago Transform your company's internal control function into a valuable strategic tool Today's companies are expected to manage a variety of risks that would have been unthinkable a decade ago. More than ever, it is vital to understand the dimensions of risk as well as how to best manage it to gain a competitive advantage. COSO Enterprise Risk Management clearly enables organizations of all types and sizes to understand and better manage their risk environments and make better decisions through use of the COSO ERM framework. A pragmatic guide for integrating ERM with COSO internal controls, this important book: Offers you expert advice on how to carry out internal control responsibilities more efficiently Updates you on the ins and outs of the COSO Report and its emergence as the new platform for understanding all aspects of risk in today's organization Shows you how an effective risk management program, following COSO ERM, can help your organization to better comply with the Sarbanes-Oxley Act Knowledgeably explains how to implement an effective ERM program COSO Enterprise Risk Management is the invaluable working resource that will show you how to identify risks, avoid pitfalls within your corporation, and keep it moving ahead of the competition. |
data governance risk management: Super Charge Your Data Warehouse Dan Linstedt, 2011-11-11 Do You Know If Your Data Warehouse Flexible, Scalable, Secure and Will It Stand The Test Of Time And Avoid Being Part Of The Dreaded Life Cycle? The Data Vault took the Data Warehouse world by storm when it was released in 2001. Some of the world's largest and most complex data warehouse situations understood the value it gave especially with the capabilities of unlimited scaling, flexibility and security. Here is what industry leaders say about the Data Vault The Data Vault is the optimal choice for modeling the EDW in the DW 2.0 framework - Bill Inmon, The Father of Data Warehousing The Data Vault is foundationally strong and an exceptionally scalable architecture - Stephen Brobst, CTO, Teradata The Data Vault should be considered as a potential standard for RDBMS-based analytic data management by organizations looking to achieve a high degree of flexibility, performance and openness - Doug Laney, Deloitte Analytics Institute I applaud Dan's contribution to the body of Business Intelligence and Data Warehousing knowledge and recommend this book be read by both data professionals and end users - Howard Dresner, From the Foreword - Speaker, Author, Leading Research Analyst and Advisor You have in your hands the work, experience and testing of 2 decades of building data warehouses. The Data Vault model and methodology has proven itself in hundreds (perhaps thousands) of solutions in Insurance, Crime-Fighting, Defense, Retail, Finance, Banking, Power, Energy, Education, High-Tech and many more. Learn the techniques and implement them and learn how to build your Data Warehouse faster than you have ever done before while designing it to grow and scale no matter what you throw at it. Ready to Super Charge Your Data Warehouse? |
data governance risk management: Corporate Governance and Risk Management in Financial Institutions Robert C. Gericke, 2018-03-27 This book presents an overview of corporate governance and risk management, analyzing their interdependence and particularly their relevance in banking. It discusses current trends in corporate governance, such as stakeholder management, financial performance and the cost of equity, compensation schemes, board structures and shareholder activism. Further, it reviews some of the most important regulatory changes introduced since the latest financial crisis and highlights their impact on the annual reports of the banks under analysis. Lastly, the book assesses and compares major banks in Brazil and Germany with special emphasis on the aspects mentioned above, revealing surprising similarities between the banking systems of these otherwise disparate countries. |
data governance risk management: DAMA-DMBOK Dama International, 2017 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. |
data governance risk management: Performance Dashboards Wayne W. Eckerson, 2005-10-27 Tips, techniques, and trends on how to use dashboard technology to optimize business performance Business performance management is a hot new management discipline that delivers tremendous value when supported by information technology. Through case studies and industry research, this book shows how leading companies are using performance dashboards to execute strategy, optimize business processes, and improve performance. Wayne W. Eckerson (Hingham, MA) is the Director of Research for The Data Warehousing Institute (TDWI), the leading association of business intelligence and data warehousing professionals worldwide that provide high-quality, in-depth education, training, and research. He is a columnist for SearchCIO.com, DM Review, Application Development Trends, the Business Intelligence Journal, and TDWI Case Studies & Solution. |
data governance risk management: Big Data Management Peter Ghavami, 2020-11-09 Data analytics is core to business and decision making. The rapid increase in data volume, velocity and variety offers both opportunities and challenges. While open source solutions to store big data, like Hadoop, offer platforms for exploring value and insight from big data, they were not originally developed with data security and governance in mind. Big Data Management discusses numerous policies, strategies and recipes for managing big data. It addresses data security, privacy, controls and life cycle management offering modern principles and open source architectures for successful governance of big data. The author has collected best practices from the world’s leading organizations that have successfully implemented big data platforms. The topics discussed cover the entire data management life cycle, data quality, data stewardship, regulatory considerations, data council, architectural and operational models are presented for successful management of big data. The book is a must-read for data scientists, data engineers and corporate leaders who are implementing big data platforms in their organizations. |
data governance risk management: Ethics, Governance and Risk Management in Organizations Intan Marzita Saidon, Roshima Said, 2020-04-06 This book brings together research works, ideas, critical reviews and strategic proposals encompassing various ethical and corporate governance issues in workplaces and organizations around the globe. For the most part, organizations are managed by policies, guidelines and systems. Good ethics and solid corporate governance help to tie these three elements together so that an effective and successful organization is established. Alongside corporate governance, ethics play an integral role in ensuring the long term survival of businesses. Multidisciplinary in approach, this book provides a platform for scholars and researchers from various backgrounds and interdisciplinary expertise to showcase their research work, ideas, critical review and strategic proposals on the ethical aspects, governance and risk management issues in organizations. The book includes discussions of ethical issues in a variety of organizations around the globe including the non-profit and non-governmental sector and also provides readers with ideas, guidelines and strategic recommendations for handling such issues. |
data governance risk management: Big Data Governance Sunil Soares, 2012 Written by a leading expert in the field, this guide focuses on the convergence of two major trends in information management--big data and information governance--by taking a strategic approach oriented around business cases and industry imperatives. With the advent of new technologies, enterprises are expanding and handling very large volumes of data; this book, nontechnical in nature and geared toward business audiences, encourages the practice of establishing appropriate governance over big data initiatives and addresses how to manage and govern big data, highlighting the relevant processes, procedures, and policies. It teaches readers to understand how big data fits within an overall information governance program; quantify the business value of big data; apply information governance concepts such as stewardship, metadata, and organization structures to big data; appreciate the wide-ranging business benefits for various industries and job functions; sell the value of big data governance to businesses; and establish step-by-step processes to implement big data governance. |
data governance risk management: Data Governance For Dummies Reichental, 2022-12-08 How to build and maintain strong data organizations—the Dummies way Data Governance For Dummies offers an accessible first step for decision makers into understanding how data governance works and how to apply it to an organization in a way that improves results and doesn't disrupt. Prep your organization to handle the data explosion (if you know, you know) and learn how to manage this valuable asset. Take full control of your organization’s data with all the info and how-tos you need. This book walks you through making accurate data readily available and maintaining it in a secure environment. It serves as your step-by-step guide to extracting every ounce of value from your data. Identify the impact and value of data in your business Design governance programs that fit your organization Discover and adopt tools that measure performance and need Address data needs and build a more data-centric business culture This is the perfect handbook for professionals in the world of data analysis and business intelligence, plus the people who interact with data on a daily basis. And, as always, Dummies explains things in terms anyone can understand, making it easy to learn everything you need to know. |
data governance risk management: Risk Management and Corporate Governance Organization for Economic Cooperation and Development, 2014 This sixth peer review of the OECD Principles of Corporate Governance analyses the corporate governance framework and practices relating to corporate risk management, in the private sector and in state-owned enterprises. The review covers 26 jurisdictions and is based on a general survey of all participating jurisdictions in December 2012, as well as an in-depth review of corporate risk management in Norway, Singapore and Switzerland. The report finds that while risk-taking is a fundamental driving force in business and entrepreneurship, the cost of risk management failures is often underestimated, both externally and internally, including the cost in terms of management time needed to rectify the situation. The reports thus concludes that corporate governance should ensure that risks are understood, managed, and, when appropriate, communicated. |
data governance risk management: Data Governance Evren Eryurek, Uri Gilad, Jessi Ashdown, Valliappa Lakshmanan, Anita Kibunguchy, 2021-04-13 As your company moves data to the cloud, you need to consider a comprehensive approach to data governance, along with well-defined and agreed-upon policies to ensure you meet compliance. Data governance incorporates the ways that people, processes, and technology work together to support business efficiency. With this practical guide, chief information, data, and security officers will learn how to effectively implement and scale data governance throughout their organizations. You'll explore how to create a strategy and tooling to support the democratization of data and governance principles. Through good data governance, you can inspire customer trust, enable your organization to extract more value from data, and generate more-competitive offerings and improvements in customer experience. This book shows you how. Enable auditable legal and regulatory compliance with defined and agreed-upon data policies Employ better risk management Establish control and maintain visibility into your company's data assets, providing a competitive advantage Drive top-line revenue and cost savings when developing new products and services Implement your organization's people, processes, and tools to operationalize data trustworthiness |
data governance risk management: The Case for the Chief Data Officer Peter Aiken, Michael M. Gorman, 2013-04-22 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 |
data governance risk management: Multi-Domain Master Data Management Mark Allen, Dalton Cervo, 2015-03-21 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. |
data governance risk management: Big Data Governance: Managing and Protecting Data Assets Michael Roberts, Big Data Governance: Managing and Protecting Data Assets offers a comprehensive exploration of the principles, practices, and strategies essential for governing vast volumes of data in the digital age. As organizations increasingly rely on big data to drive decision-making and innovation, effective governance becomes paramount to ensure data quality, security, and compliance. This book delves into key topics such as data governance frameworks, privacy regulations, risk management, and ethical considerations. Whether you're a data steward, IT manager, compliance officer, or business leader, this handbook equips you with the insights and tools to establish robust data governance frameworks and safeguard your organization's most valuable asset—its data. |
data governance risk management: Global Risk Governance Ortwin Renn, Katherine D. Walker, 2008-12-18 The establishment of the International Risk Governance Council (IRGC) was the direct result of widespread concern that the complexity and interdependence of health, environmental, and technological risks facing the world was making the development and implementation of adequate risk governance strategies ever more difficult. This volume details the IRGC developed and proposed framework for risk governance and covers how it was peer reviewed as well as tested |
data governance risk management: The Law of Governance, Risk Management, and Compliance Geoffrey P. Miller, 2017 The second edition of The Law of Governance, Risk Management, and Compliance follows the first edition, as the first casebook focused on the law of governance, risk management, and compliance. Author Geoffrey P. Miller, a highly respected professor of corporate and financial law, brings real world experience to the book as a member of the board of directors and audit and risk committees of a significant banking institution. The book addresses issues of fundamental importance for any regulated organization (the $13 billion settlement between JPMorgan Chase and its regulators is only one of many examples). This book can be a cornerstone for courses on compliance, corporate governance, or on the role of attorneys in managing risk in organizational clients. |
data governance risk management: Driving Digital Isaac Sacolick, 2017-08-24 Every organization makes plans for updating products, technologies, and business processes. But that’s not enough anymore for the twenty-first-century company. The race is now on for everyone to become a digital enterprise. For those individuals who have been charged with leading their company’s technology-driven change, the pressure is intense while the correct path forward unclear. Help has arrived! In Driving Digital, author Isaac Sacolick shares the lessons he’s learned over the years as he has successfully spearheaded multiple transformations and helped shape digital-business best practices. Readers no longer have to blindly trek through the mine field of their company’s digital transformation. In this thoroughly researched one-stop manual, learn how to: • Formulate a digital strategy • Transform business and IT practices • Align development and operations • Drive culture change • Bolster digital talent • Capture and track ROI • Develop innovative digital practices • Pilot emerging technologies • And more! Your company cannot avoid the digital disruption heading its way. The choice is yours: Will this mean the beginning of the end for your business, or will your digital practices be what catapults you into next-level success? |
data governance risk management: Governance, Risk, and Compliance Handbook Anthony Tarantino, 2008-03-11 Providing a comprehensive framework for a sustainable governance model, and how to leverage it in competing global markets, Governance, Risk, and Compliance Handbook presents a readable overview to the political, regulatory, technical, process, and people considerations in complying with an ever more demanding regulatory environment and achievement of good corporate governance. Offering an international overview, this book features contributions from sixty-four industry experts from fifteen countries. |
data governance risk management: 99 Privacy Breaches to Beware Of: Practical Data Protection Tips from Real Life Experiences Kevin Shepherdson, William Hioe, Lynn Boxall, 2018-08-15 Data protection laws are new in Singapore, Malaysia, Philippines, Indonesia and Thailand. In Europe, the General Data Protection Regulation (GDPR) — a single law across all of EU – comes into force from May 2018. There are also strict laws in the US that govern the processing of personal data. Over a hundred countries in the world have a comprehensive data protection law and it is very easy for individuals and companies to breach these laws. Data or privacy breaches are on the rise and businesses can be prosecuted under data protection laws. Fines for non-compliance can be from S$1 million in Singapore, up to three years jail in Malaysia, and up to 4% of global revenues for EU countries. The focus on this book is operational compliance. The book is for everyone as all of us in the course of our daily work process personal data. Organised into sections, each idea provides practical advice and examples of how a breach of the law may happen. Examples cover HR, Finance, Admin, Marketing, etc, allowing the reader to relate to his or her own area of work |
data governance risk management: Self-Service Data Analytics and Governance for Managers Nathan E. Myers, Gregory Kogan, 2021-06-02 Project governance, investment governance, and risk governance precepts are woven together in Self-Service Data Analytics and Governance for Managers, equipping managers to structure the inevitable chaos that can result as end-users take matters into their own hands Motivated by the promise of control and efficiency benefits, the widespread adoption of data analytics tools has created a new fast-moving environment of digital transformation in the finance, accounting, and operations world, where entire functions spend their days processing in spreadsheets. With the decentralization of application development as users perform their own analysis on data sets and automate spreadsheet processing without the involvement of IT, governance must be revisited to maintain process control in the new environment. In this book, emergent technologies that have given rise to data analytics and which form the evolving backdrop for digital transformation are introduced and explained, and prominent data analytics tools and capabilities will be demonstrated based on real world scenarios. The authors will provide a much-needed process discovery methodology describing how to survey the processing landscape to identify opportunities to deploy these capabilities. Perhaps most importantly, the authors will digest the mature existing data governance, IT governance, and model governance frameworks, but demonstrate that they do not comprehensively cover the full suite of data analytics builds, leaving a considerable governance gap. This book is meant to fill the gap and provide the reader with a fit-for-purpose and actionable governance framework to protect the value created by analytics deployment at scale. Project governance, investment governance, and risk governance precepts will be woven together to equip managers to structure the inevitable chaos that can result as end-users take matters into their own hands. |
data governance risk management: Information Security Risk Management for ISO 27001/ISO 27002, third edition Alan Calder, Steve Watkins, 2019-08-29 Ideal for risk managers, information security managers, lead implementers, compliance managers and consultants, as well as providing useful background material for auditors, this book will enable readers to develop an ISO 27001-compliant risk assessment framework for their organisation and deliver real, bottom-line business benefits. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …