Download or read book Data Stewardship written by David Plotkin and published by Newnes. This book was released on 2013-09-16 with total page 251 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data stewards in business and IT are the backbone of a successful data governance implementation because they do the work to make a company's data trusted, dependable, and high quality. Data Stewardship explains everything you need to know to successfully implement the stewardship portion of data governance, including how to organize, train, and work with data stewards, get high-quality business definitions and other metadata, and perform the day-to-day tasks using a minimum of the steward's time and effort. David Plotkin has loaded this book with practical advice on stewardship so you can get right to work, have early successes, and measure and communicate those successes, gaining more support for this critical effort. - Provides clear and concise practical advice on implementing and running data stewardship, including guidelines on how to organize based on company structure, business functions, and data ownership - Shows how to gain support for your stewardship effort, maintain that support over the long-term, and measure the success of the data stewardship effort and report back to management - Includes detailed lists of responsibilities for each type of data steward and strategies to help the Data Governance Program Office work effectively with the data stewards

Download or read book Data Governance written by John Ladley and published by Academic Press. This book was released on 2019-11-08 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Executing Data Quality Projects written by Danette McGilvray and published by Academic Press. This book was released on 2021-05-27 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Executing Data Quality Projects, Second Edition presents a structured yet flexible approach for creating, improving, sustaining and managing the quality of data and information within any organization. Studies show that data quality problems are costing businesses billions of dollars each year, with poor data linked to waste and inefficiency, damaged credibility among customers and suppliers, and an organizational inability to make sound decisions. Help is here! This book describes a proven Ten Step approach that combines a conceptual framework for understanding information quality with techniques, tools, and instructions for practically putting the approach to work – with the end result of high-quality trusted data and information, so critical to today's data-dependent organizations. The Ten Steps approach applies to all types of data and all types of organizations – for-profit in any industry, non-profit, government, education, healthcare, science, research, and medicine. This book includes numerous templates, detailed examples, and practical advice for executing every step. At the same time, readers are advised on how to select relevant steps and apply them in different ways to best address the many situations they will face. The layout allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, best practices, and warnings. The experience of actual clients and users of the Ten Steps provide real examples of outputs for the steps plus highlighted, sidebar case studies called Ten Steps in Action. This book uses projects as the vehicle for data quality work and the word broadly to include: 1) focused data quality improvement projects, such as improving data used in supply chain management, 2) data quality activities in other projects such as building new applications and migrating data from legacy systems, integrating data because of mergers and acquisitions, or untangling data due to organizational breakups, and 3) ad hoc use of data quality steps, techniques, or activities in the course of daily work. The Ten Steps approach can also be used to enrich an organization's standard SDLC (whether sequential or Agile) and it complements general improvement methodologies such as six sigma or lean. No two data quality projects are the same but the flexible nature of the Ten Steps means the methodology can be applied to all. The new Second Edition highlights topics such as artificial intelligence and machine learning, Internet of Things, security and privacy, analytics, legal and regulatory requirements, data science, big data, data lakes, and cloud computing, among others, to show their dependence on data and information and why data quality is more relevant and critical now than ever before. - Includes concrete instructions, numerous templates, and practical advice for executing every step of The Ten Steps approach - Contains real examples from around the world, gleaned from the author's consulting practice and from those who implemented based on her training courses and the earlier edition of the book - Allows for quick reference with an easy-to-use format highlighting key concepts and definitions, important checkpoints, communication activities, and best practices - A companion Web site includes links to numerous data quality resources, including many of the templates featured in the text, quick summaries of key ideas from the Ten Steps methodology, and other tools and information that are available online

Download or read book Data Governance The Definitive Guide written by Evren Eryurek and published by "O'Reilly Media, Inc.". This book was released on 2021-03-08 with total page 254 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book DAMA DMBOK written by Dama International and published by . This book was released on 2017 with total page 628 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book A Practitioner s Guide to Data Governance written by Uma Gupta and published by Emerald Group Publishing. This book was released on 2020-07-08 with total page 115 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data governance looks simple on paper, but in reality it is a complex issue facing organizations. In this practical guide, data experts Uma Gupta and San Cannon look to demystify data governance through pragmatic advice based on real-world experience and cutting-edge academic research.

Download or read book Data Governance written by Evren Eryurek and published by . This book was released on 2021-04-13 with total page 300 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Information Governance written by Robert F. Smallwood and published by John Wiley & Sons. This book was released on 2014-03-28 with total page 464 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Navigating the Labyrinth written by Laura Sebastian-Coleman and published by Technics Publications. This book was released on with total page 123 pages. Available in PDF, EPUB and Kindle. Book excerpt: An Executive Guide to Data Management

Download or read book Disrupting Data Governance written by Laura Madsen and published by . This book was released on 2019-12-06 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data governance is broken. It's time we fix it. Why is data governance so ineffective? The truth is data governance programs aren't designed for the way we run our data teams they aren't even designed for a modern organization at all. They were designed when reports still came through inter-office mail. The flow of data into within and out of today's organizations is a tsunami breaking through rigid data governance methods. Yet our programs still rely on that command and control approach. Have you ever tried to control a tsunami? Every organization that uses data knows that they need a data governance program. Data literacy efforts and legislation like GDPR have become the bellwethers for our governance functions. But we still sit in data governance meetings without enough people and too many questions to move things forward. There's no agility to the program because we imply a degree of frailty to the data that doesn't exist. We continue to insist on archaic methods that bring no value to our organizations. Achieving deep insights from data can't happen without good governance practices. Laura Madsen shows you how to redefine governance for the modern age. With a casual witty style Madsen taps on her decades of experience shares interviews with other best-in-field experts and grounds her perspective in research. Witness where it all fell apart challenge long-held beliefs and commit to a fundamental shift--that governance is not about stopping or preventing usage but about supporting the usage of data. Be able to bring back trust and value to our data governance functions and learn the: People-driven approach to governance Processes that support the tsunami of data Cutting edge technology that's enabling data governance

Download or read book Data Governance written by Dimitrios Sargiotis and published by Springer Nature. This book was released on with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Governance of Data written by Alison Holt and published by BCS, The Chartered Institute for IT. This book was released on 2018-11-28 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data is fundamentally changing the nature of businesses and organisations, and the mechanisms for delivering products and services. This book is a practical guide to developing strategy and policy for data governance, in line with the developing ISO 38505 governance of data standards. It will assist an organisation wanting to become more of a data driven business by explaining how to assess the value, risks and constraints associated with collecting, using and distributing data.

Download or read book Non Invasive Data Governance written by Robert S. Seiner and published by Technics Publications. This book was released on 2014-09-01 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book The DAMA Dictionary of Data Management written by Dama International and published by . This book was released on 2011 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Data Mining Concepts and Techniques written by Jiawei Han and published by Elsevier. This book was released on 2011-06-09 with total page 740 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining: Concepts and Techniques provides the concepts and techniques in processing gathered data or information, which will be used in various applications. Specifically, it explains data mining and the tools used in discovering knowledge from the collected data. This book is referred as the knowledge discovery from data (KDD). It focuses on the feasibility, usefulness, effectiveness, and scalability of techniques of large data sets. After describing data mining, this edition explains the methods of knowing, preprocessing, processing, and warehousing data. It then presents information about data warehouses, online analytical processing (OLAP), and data cube technology. Then, the methods involved in mining frequent patterns, associations, and correlations for large data sets are described. The book details the methods for data classification and introduces the concepts and methods for data clustering. The remaining chapters discuss the outlier detection and the trends, applications, and research frontiers in data mining. This book is intended for Computer Science students, application developers, business professionals, and researchers who seek information on data mining. - Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects - Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields - Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data

Download or read book Data Governance written by Harkish Sen and published by . This book was released on 2019 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: What is data governance? And what are the principles and techniques you can leverage as a business or IT professional to make data governance successful within your organization? Data Governance will answer these questions and provide you with insights and approaches to improve the "data fitness" of your organization. Gain control of your data and assign responsible parties to ensure the data remains well-understood and protected, by applying the content within this book's six chapters: Chapter 1, Understanding Data Governance, looks at the broad definitions of data governance along with issues within data governance. Chapter 2, Owning Data Governance, looks at Ownership, Wider Perspectives, and Roles, and explores how transparent data governance can simplify the complexities of data ownership. Chapter 3, Data Confidence, explores using tools (e.g., standards, strategies, and policies) to clearly align business objectives with realistic IT deliverables and produce meaningful outcomes. Chapter 4, Getting Data Fit, covers the basic elements required to make data governance work for your specific organization. There are five steps required to achieve a basic level of data fitness and effective governance. Chapter 5, Approach and Stakeholders, covers various ways to implement data governance to ensure there are clear milestones and trigger points for key stakeholders to approve each phase. A data scorecard is introduced as a tool to help guide an organization through the data governance process. Chapter 6, A Case Study, concerns a fictitious company, D474, used to illustrate the various examples and scenarios for implementing data governance.

Download or read book Data Quality written by Rupa Mahanti and published by Quality Press. This book was released on 2019-03-18 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: “This is not the kind of book that you’ll read one time and be done with. So scan it quickly the first time through to get an idea of its breadth. Then dig in on one topic of special importance to your work. Finally, use it as a reference to guide your next steps, learn details, and broaden your perspective.” from the foreword by Thomas C. Redman, Ph.D., “the Data Doc” Good data is a source of myriad opportunities, while bad data is a tremendous burden. Companies that manage their data effectively are able to achieve a competitive advantage in the marketplace, while bad data, like cancer, can weaken and kill an organization. In this comprehensive book, Rupa Mahanti provides guidance on the different aspects of data quality with the aim to be able to improve data quality. Specifically, the book addresses: -Causes of bad data quality, bad data quality impacts, and importance of data quality to justify the case for data quality-Butterfly effect of data quality-A detailed description of data quality dimensions and their measurement-Data quality strategy approach-Six Sigma - DMAIC approach to data quality-Data quality management techniques-Data quality in relation to data initiatives like data migration, MDM, data governance, etc.-Data quality myths, challenges, and critical success factorsStudents, academicians, professionals, and researchers can all use the content in this book to further their knowledge and get guidance on their own specific projects. It balances technical details (for example, SQL statements, relational database components, data quality dimensions measurements) and higher-level qualitative discussions (cost of data quality, data quality strategy, data quality maturity, the case made for data quality, and so on) with case studies, illustrations, and real-world examples throughout.