| dama dmbok data management body of knowledge: 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. |
| dama dmbok data management body of knowledge: The DAMA Guide to the Data Management Body of Knowledge Mark Mosley, 2010 Written by over 120 data management practitioners, this is the most impressive compilation of data management principals and best practices, ever assembled. It provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure. The equivalent of the PMBOK or the BABOK, the DAMA-DMBOK provides information on: Data Governance; Data Architecture Management; Data Development; Database Operations Management; Data Security Management; Reference & Master Data Management; Data Warehousing & Business Intelligence Management; Document & Content Management; Meta Data Management; Data Quality Management; Professional Development. As an authoritative introduction to data management, the goals of the DAMA-DMBOK Guide are: To build consensus for a generally applicable view of data management functions; To provide standard definitions for commonly used data management functions, deliverables, roles, and other terminology; To document guiding principles for data management; To present a vendor-neutral overview to commonly accepted good practices, widely adopted methods and techniques, and significant alternative approaches; To clarify the scope and boundaries of data management; To act as a reference which guides readers to additional resources for further understanding. |
| dama dmbok data management body of knowledge: DAMA-DMBOK Data Management Association, 2017 The second edition of DAMA International's Guide to the Data Management Body of Knowledge (DAMA-DMBOK2) updates and augments the highly successful DMBOK1. An accessible, authoritative reference book written by leading thinkers in the field and extensively reviewed by DAMA members, DMBOK2 brings together materials that comprehensively describe the challenges of data management and how to meet them by: 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, including the 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.--Publisher description |
| dama dmbok data management body of knowledge: Data Management at Scale Piethein Strengholt, 2020-07-29 As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, you’ll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the modern world of data consumption. Executives, data architects, analytics teams, and compliance and governance staff will learn how to build a modern scalable data landscape using the Scaled Architecture, which you can introduce incrementally without a large upfront investment. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including technological developments, regulatory requirements, and privacy concerns Go deep into the Scaled Architecture and learn how the pieces fit together Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata |
| dama dmbok data management body of knowledge: 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 |
| dama dmbok data management body of knowledge: Navigating the Labyrinth Laura Sebastian-Coleman, An Executive Guide to Data Management |
| dama dmbok data management body of knowledge: The DAMA Guide to the Data Management Body of Knowledge DAMA International, 2009-04 This is the definitive introduction to the field of data management. Use this guide to build consensus, introduce standard definitions, and identify guiding principles for data management gement functions, roles, and deliverables. DAMA-DMBOK references the DAMA Dictionary of Data Management. Under the umbrella and support of the non-profit association DAMA International, the DAMA International Foundation is a 501 c (6) not-for-profit entity, whose mission is to foster the advancement of the data management profession and community through education and research. By purchasing this indispensable piece of knowledge you will continue to support the data management community. |
| dama dmbok data management body of knowledge: Enterprise Master Data Management Allen Dreibelbis, Eberhard Hechler, Ivan Milman, Martin Oberhofer, Paul van Run, Dan Wolfson, 2008-06-05 The Only Complete Technical Primer for MDM Planners, Architects, and Implementers Companies moving toward flexible SOA architectures often face difficult information management and integration challenges. The master data they rely on is often stored and managed in ways that are redundant, inconsistent, inaccessible, non-standardized, and poorly governed. Using Master Data Management (MDM), organizations can regain control of their master data, improve corresponding business processes, and maximize its value in SOA environments. Enterprise Master Data Management provides an authoritative, vendor-independent MDM technical reference for practitioners: architects, technical analysts, consultants, solution designers, and senior IT decisionmakers. Written by the IBM ® data management innovators who are pioneering MDM, this book systematically introduces MDM’s key concepts and technical themes, explains its business case, and illuminates how it interrelates with and enables SOA. Drawing on their experience with cutting-edge projects, the authors introduce MDM patterns, blueprints, solutions, and best practices published nowhere else—everything you need to establish a consistent, manageable set of master data, and use it for competitive advantage. Coverage includes How MDM and SOA complement each other Using the MDM Reference Architecture to position and design MDM solutions within an enterprise Assessing the value and risks to master data and applying the right security controls Using PIM-MDM and CDI-MDM Solution Blueprints to address industry-specific information management challenges Explaining MDM patterns as enablers to accelerate consistent MDM deployments Incorporating MDM solutions into existing IT landscapes via MDM Integration Blueprints Leveraging master data as an enterprise asset—bringing people, processes, and technology together with MDM and data governance Best practices in MDM deployment, including data warehouse and SAP integration |
| dama dmbok data management body of knowledge: MASTER DATA MANAGEMENT AND DATA GOVERNANCE, 2/E Alex Berson, Larry Dubov, 2010-12-06 The latest techniques for building a customer-focused enterprise environment The authors have appreciated that MDM is a complex multidimensional area, and have set out to cover each of these dimensions in sufficient detail to provide adequate practical guidance to anyone implementing MDM. While this necessarily makes the book rather long, it means that the authors achieve a comprehensive treatment of MDM that is lacking in previous works. -- Malcolm Chisholm, Ph.D., President, AskGet.com Consulting, Inc. Regain control of your master data and maintain a master-entity-centric enterprise data framework using the detailed information in this authoritative guide. Master Data Management and Data Governance, Second Edition provides up-to-date coverage of the most current architecture and technology views and system development and management methods. Discover how to construct an MDM business case and roadmap, build accurate models, deploy data hubs, and implement layered security policies. Legacy system integration, cross-industry challenges, and regulatory compliance are also covered in this comprehensive volume. Plan and implement enterprise-scale MDM and Data Governance solutions Develop master data model Identify, match, and link master records for various domains through entity resolution Improve efficiency and maximize integration using SOA and Web services Ensure compliance with local, state, federal, and international regulations Handle security using authentication, authorization, roles, entitlements, and encryption Defend against identity theft, data compromise, spyware attack, and worm infection Synchronize components and test data quality and system performance |
| dama dmbok data management body of knowledge: 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. |
| dama dmbok data management body of knowledge: Data Stewardship David Plotkin, 2013-09-16 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 |
| dama dmbok data management body of knowledge: The Practitioner's Guide to Data Quality Improvement David Loshin, 2010-11-22 The Practitioner's Guide to Data Quality Improvement offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. It shares the fundamentals for understanding the impacts of poor data quality, and guides practitioners and managers alike in socializing, gaining sponsorship for, planning, and establishing a data quality program. It demonstrates how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. It includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning. This book is recommended for data management practitioners, including database analysts, information analysts, data administrators, data architects, enterprise architects, data warehouse engineers, and systems analysts, and their managers. - Offers a comprehensive look at data quality for business and IT, encompassing people, process, and technology. - Shows how to institute and run a data quality program, from first thoughts and justifications to maintenance and ongoing metrics. - Includes an in-depth look at the use of data quality tools, including business case templates, and tools for analysis, reporting, and strategic planning. |
| dama dmbok data management body of knowledge: The Effective Change Manager The Change Management Institute, 2022-04-27 'The Effective Change Manager' is designed for change management practitioners, employers, authors, academics and anyone with an interest in the evolving professional discipline of change management. The first edition, 'The Change Management Body of Knowledge (CMBoK©)', drew on the experience of more than six hundred change management professionals in thirty countries. This second edition has grown that base to over 900 contributors and reviewers. 'The Effective Change Manager' describes the underpinning knowledge areas that change managers must know and understand to be effective in their change practice. It also describes the evolution of the change management practice as it starts to mature. The Change Management Institute operates as a global leader in strengthening, connecting and advancing the change management profession. It is committed to assisting members in developing Capability, Credibility and Connections in their pursuit of professional excellence. The Change Management Institute is an independent professional organization that is uniquely positioned to promote and advance the interests of Change Management. |
| dama dmbok data management body of knowledge: Data Management: a gentle introduction Bas van Gils, 2020-03-03 The overall objective of this book is to show that data management is an exciting and valuable capability that is worth time and effort. More specifically it aims to achieve the following goals: 1. To give a “gentle” introduction to the field of DM by explaining and illustrating its core concepts, based on a mix of theory, practical frameworks such as TOGAF, ArchiMate, and DMBOK, as well as results from real-world assignments. 2. To offer guidance on how to build an effective DM capability in an organization.This is illustrated by various use cases, linked to the previously mentioned theoretical exploration as well as the stories of practitioners in the field. The primary target groups are: busy professionals who “are actively involved with managing data”. The book is also aimed at (Bachelor’s/ Master’s) students with an interest in data management. The book is industry-agnostic and should be applicable in different industries such as government, finance, telecommunications etc. Typical roles for which this book is intended: data governance office/ council, data owners, data stewards, people involved with data governance (data governance board), enterprise architects, data architects, process managers, business analysts and IT analysts. The book is divided into three main parts: theory, practice, and closing remarks. Furthermore, the chapters are as short and to the point as possible and also make a clear distinction between the main text and the examples. If the reader is already familiar with the topic of a chapter, he/she can easily skip it and move on to the next. |
| dama dmbok data management body of knowledge: The Dama Guide to the Data Management Body of Knowledge (Japanese edition) Dama International, 2009-04-01 Written by over 120 data management practitioners, the DAMA Guide to the Data Management Body of Knowledge (DAMA-DMBOK) is the most impressive compilation of data management principals and best practices, ever assembled. It provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure. The equivalent of the PMBOK or the BABOK, the DAMA-DMBOK provides information on: • Data Governance • Data Architecture Management • Data Development • Database Operations Management • Data Security Management • Reference & Master Data Management • Data Warehousing & Business Intelligence Management • Document & Content Management • Meta Data Management • Data Quality Management • Professional Development As an authoritative introduction to data management, the goals of the DAMA-DMBOK Guide are: • To build consensus for a generally applicable view of data management functions.• To provide standard definitions for commonly used data management functions, deliverables, roles, and other terminology.• To document guiding principles for data management.• To present a vendor-neutral overview to commonly accepted good practices, widely adopted methods and techniques, and significant alternative approaches.• To clarify the scope and boundaries of data management.• To act as a reference which guides readers to additional resources for further understanding. The Editors are Mark Mosley, Editor - Development, Michael Brackett, Editor - Production, Susan Early, Assistant Editor, and Deborah Henderson, Project Sponsor. The Foreword is by John Zachman (DAMA I Lifetime Achievement Award recipient), the Preface is by John Schley (DAMA International President) and Deborah Henderson (DAMA Foundation President, DAMA International VP Education and Research), and the Afterword is by Michael Brackett (DAMA International Lifetime Achievement Award recipient). From the Foreword by John Zachman: The book is an exhaustive compilation of every possible subject and issue that warrants consideration in initiating and operating a Data Management responsibility in a modern Enterprise. It is impressive in its comprehensiveness. It not only identifies the goals and objectives of every Data Management issue and responsibility but it also suggests the natural organizational participants and end results that should be expected.The publication began as a non-trivial, sorely needed compilation of articles and substantive facts about the little understood subject of data management orchestrated by some folks from the DAMA Chicago Chapter. It was unique at the time as there was little substantive reference material on the subject. It has grown to become this pragmatic practitioner's handbook that deserves a place on every Data Management professional's bookshelf. There is a wealth of information for the novice data beginner, but it is also invaluable to the old timer as a check-list and validation of their understanding and responsibilities to ensure that nothing “falls through the cracks”! It is impressive in it breadth and completeness.The DAMA-DMBOK Guide deserves a place on every Data Management professional's bookshelf and for the General Manager, it will serve as a guide for setting expectations and assigning responsibilities for managing and practicing what has become the very most critical resource owned by an Enterprise as it (the Enterprise) progresses into the Information Age: DATA! |
| dama dmbok data management body of knowledge: Measuring Data Quality for Ongoing Improvement Laura Sebastian-Coleman, 2012-12-31 The Data Quality Assessment Framework shows you how to measure and monitor data quality, ensuring quality over time. You'll start with general concepts of measurement and work your way through a detailed framework of more than three dozen measurement types related to five objective dimensions of quality: completeness, timeliness, consistency, validity, and integrity. Ongoing measurement, rather than one time activities will help your organization reach a new level of data quality. This plain-language approach to measuring data can be understood by both business and IT and provides practical guidance on how to apply the DQAF within any organization enabling you to prioritize measurements and effectively report on results. Strategies for using data measurement to govern and improve the quality of data and guidelines for applying the framework within a data asset are included. You'll come away able to prioritize which measurement types to implement, knowing where to place them in a data flow and how frequently to measure. Common conceptual models for defining and storing of data quality results for purposes of trend analysis are also included as well as generic business requirements for ongoing measuring and monitoring including calculations and comparisons that make the measurements meaningful and help understand trends and detect anomalies. - Demonstrates how to leverage a technology independent data quality measurement framework for your specific business priorities and data quality challenges - Enables discussions between business and IT with a non-technical vocabulary for data quality measurement - Describes how to measure data quality on an ongoing basis with generic measurement types that can be applied to any situation |
| dama dmbok data management body of knowledge: Mastering Your Data Andy Graham, 2015-01-01 This is my latest book on Data Architecture focusing on the subject of MDM (Master Data Management). It is intended to provide a overview of the subject with chapters covering key topics such as: the business case, data privacy, the challenges of global MDM, golden source and authoritative source explanations, the different MDM styles and the record matching process. The back cover text says the following: Master Data Management (MDM for short) has become a whole industry, within an industry. There are many companies now claiming to be MDM software (or services) providers. Everyone wants a master data project on their CV, and in general it has become hip and trendy to talk about and do. The reality is that MDM is in fact the reincarnation of the problem of how to manage the consistency and integrity of the myriads of data assets that exist across the enterprise. This book provides an understanding of MDM, the business drivers behind it, the various techniques that are critical to its success and gives a good architectural grounding in the subject. It is perfect for anyone embarking on an ‘adventure’ in this problem space. I hope you find this book enjoyable and useful. Andy |
| dama dmbok data management body of knowledge: DAMA-DMBOK, Italian Version Dama International, 2020-04-03 Il Data Management Body of Knowledge (DAMA-DMBOK2) presenta una vista complessiva delle sfide, complessità e valore di un'efficace gestione dei dati. Le organizzazioni odierne riconoscono che la gestione dei dati è fondamentale per il loro successo. Riconoscono il valore dei loro dati e cercano di sfruttare tale valore. Con l'aumento della nostra capacità di creare e sfruttare i dati, aumenta anche la necessità di pratiche affidabili di gestione dei dati. La seconda edizione della Guida di DAMA International al Data Management Body of Knowledge (DAMA-DMBOK2) aggiorna e accresce il DMBOK1, che ha avuto grande successo. Libro di riferimento accessibile e autorevole scritto da pensatori leader del settore e ampiamente recensito dai membri DAMA, il DMBOK2 riunisce materiali che descrivono in modo esaustivo le sfide del data management e come affrontarle: Definendo una serie di principi guida per il data management e descrivendo come questi principi possono essere applicati all'interno delle aree funzionali del data management. Fornendo un framework funzionale per l'implementazione dell'enterprise data management, includendo pratiche ampiamente adottate, metodi e tecniche, funzioni, ruoli deliverable e metriche. Stabilendo un vocabolario comune per i concetti del data management e fornendo il fondamento delle best practice per i data management professional. |
| dama dmbok data management body of knowledge: The DAMA Guide to the Data Management Body of Knowledge Enterprise Server Version Dama International, 2009-04-01 Written by over 120 data management practitioners, the DAMA Guide to the Data Management Body of Knowledge (DAMA-DMBOK) is the most impressive compilation of data management principals and best practices, ever assembled. It provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure. The equivalent of the PMBOK or the BABOK, the DAMA-DMBOK provides information on: Data Governance Data Architecture Management Data Development Database Operations Management Data Security Management Reference |
| dama dmbok data management body of knowledge: Head First Agile Andrew Stellman, Jennifer Greene, 2017-09-18 Head First Agile is a complete guide to learning real-world agile ideas, practices, principles. What will you learn from this book? In Head First Agile, you'll learn all about the ideas behind agile and the straightforward practices that drive it. You'll take deep dives into Scrum, XP, Lean, and Kanban, the most common real-world agile approaches today. You'll learn how to use agile to help your teams plan better, work better together, write better code, and improve as a team—because agile not only leads to great results, but agile teams say they also have a much better time at work. Head First Agile will help you get agile into your brain... and onto your team! Preparing for your PMI-ACP® certification? This book also has everything you need to get certified, with 100% coverage of the PMI-ACP® exam. Luckily, the most effective way to prepare for the exam is to get agile into your brain—so instead of cramming, you're learning. Why does this book look so different? Based on the latest research in cognitive science and learning theory, Head First Agile uses a visually rich format to engage your mind, rather than a text-heavy approach that puts you to sleep. Why waste your time struggling with new concepts? This multi-sensory learning experience is designed for the way your brain really works. |
| dama dmbok data management body of knowledge: Advances in Conceptual Modeling Giancarlo Guizzardi, Frederik Gailly, Rita Suzana Pitangueira Maciel, 2019-10-26 This book constitutes the refereed proceedings of five workshops symposia, held at the 38th International Conference on Conceptual Modeling, ER 2019, in Salvador, Brazil, in November 2019. The 34 papers promote and disseminate research on theories of concepts underlying conceptual modeling, methods and tools for developing and communicating conceptual models, techniques for transforming conceptual models into effective implementations, and the impact of conceptual modeling techniques on databases, business strategies and information systems. The following workshops are included in this volume: Workshop on Conceptual Modeling, Ontologies and Metadata Management for FAIR Data (FAIR), 6th Workshop on Conceptual Modeling in Requirements Engineering and Business Analysis (MREBA), 2nd International Workshop on Empirical Methods in Conceptual Modeling (EmpER), 8th International Workshop on Modeling and Management of Big Data (MoBiD19), and 7th International Workshop on Ontologies andConceptual Modelling (OntoCom). |
| dama dmbok data management body of knowledge: CDMP - Data Management Fundamentals Exam Questions on DMBOK2 (2nd Edition) Data Management Professor, 2021-05-20 Have you already taken a CDMP (Certified Data Management Professional) Data Management Fundamentals course from a Registered Training Provider? Or Have you self-studied using the DAMA DMBOK 2? Are you still not quite confident that you are ready to take the certification exam? If so, you've come to the right place! 290 Questions covering all the chapters of DMBOK2 as well as 2 x 100 question practice exams. Also see the dedicated notebook to assist you when studying for the CDMP Exam: https://www.amazon.com/dp/B09B46WKXJ |
| dama dmbok data management body of knowledge: 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. |
| dama dmbok data management body of knowledge: Data Quality Jack E. Olson, 2003-01-09 Data Quality: The Accuracy Dimension is about assessing the quality of corporate data and improving its accuracy using the data profiling method. Corporate data is increasingly important as companies continue to find new ways to use it. Likewise, improving the accuracy of data in information systems is fast becoming a major goal as companies realize how much it affects their bottom line. Data profiling is a new technology that supports and enhances the accuracy of databases throughout major IT shops. Jack Olson explains data profiling and shows how it fits into the larger picture of data quality.* Provides an accessible, enjoyable introduction to the subject of data accuracy, peppered with real-world anecdotes. * Provides a framework for data profiling with a discussion of analytical tools appropriate for assessing data accuracy. * Is written by one of the original developers of data profiling technology. * Is a must-read for any data management staff, IT management staff, and CIOs of companies with data assets. |
| dama dmbok data management body of knowledge: Modern Data Strategy Mike Fleckenstein, Lorraine Fellows, 2018-02-12 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. |
| dama dmbok data management body of knowledge: Data as a Service Pushpak Sarkar, 2015-07-31 Data as a Service shows how organizations can leverage “data as a service” by providing real-life case studies on the various and innovative architectures and related patterns Comprehensive approach to introducing data as a service in any organization A reusable and flexible SOA based architecture framework Roadmap to introduce ‘big data as a service’ for potential clients Presents a thorough description of each component in the DaaS reference architecture so readers can implement solutions |
| dama dmbok data management body of knowledge: The Data Management Toolkit: A Step-By-Step Implementation Guide for the Pioneers of Data Management Irina Steenbeek, 2019-03-09 Eight years ago, I joined a new company. My first challenge was to develop an automated management accounting reporting system. A deep analysis of the existing reports showed us the high necessity to implement a singular reporting platform, and we opted to implement a data warehouse. At the time, one of the consultants came to me and said, I heard that we might need data management. I don't know what it is. Check it out. So I started Googling Data management...This book is for professionals who are now in the same position I found myself in eight years ago and for those who want to become a data management pro of a medium sized company.It is a collection of hands-on knowledge, experience and observations on how to implement data management in an effective, feasible and to-the-point way. |
| dama dmbok data management body of knowledge: The Data Science Framework Juan J. Cuadrado-Gallego, Yuri Demchenko, 2020-10-01 This edited book first consolidates the results of the EU-funded EDISON project (Education for Data Intensive Science to Open New science frontiers), which developed training material and information to assist educators, trainers, employers, and research infrastructure managers in identifying, recruiting and inspiring the data science professionals of the future. It then deepens the presentation of the information and knowledge gained to allow for easier assimilation by the reader. The contributed chapters are presented in sequence, each chapter picking up from the end point of the previous one. After the initial book and project overview, the chapters present the relevant data science competencies and body of knowledge, the model curriculum required to teach the required foundations, profiles of professionals in this domain, and use cases and applications. The text is supported with appendices on related process models. The book can be used to develop new courses in data science, evaluate existing modules and courses, draft job descriptions, and plan and design efficient data-intensive research teams across scientific disciplines. |
| dama dmbok data management body of knowledge: The "Orange" Model of Data Management Irina Steenbeek, 2019-10-21 *This book is a brief overview of the model and has only 24 pages.*Almost every data management professional, at some point in their career, has come across the following crucial questions:1. Which industry reference model should I use for the implementation of data managementfunctions?2. What are the key data management capabilities that are feasible and applicable to my company?3. How do I measure the maturity of the data management functions and compare that withthose of my peers in the industry4. What are the critical, logical steps in the implementation of data management?The Orange (meta)model of data management provides a collection of techniques and templates for the practical set up of data management through the design and implementation of the data and information value chain, enabled by a set of data management capabilities.This book is a toolkit for advanced data management professionals and consultants thatare involved in the data management function implementation.This book works together with the earlier published The Data Management Toolkit. The Orange model assists in specifying the feasible scope of data management capabilities, that fits company's business goals and resources. The Data Management Toolkit is a practical implementation guide of the chosen data management capabilities. |
| dama dmbok data management body of knowledge: Disrupting Data Governance Laura Madsen, 2019-12-06 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 |
| dama dmbok data management body of knowledge: The Chief Data Officer's Playbook Caroline Carruthers, Peter Jackson, 2020-12-20 This fully revised and updated edition of the bestselling Chief Data Officer’s Playbook offers new insights into the role of the CDO and the data environment. Written by two of the world’s leading experts in data driven transformation, it addresses the changes that have taken place in ‘data’, in the role of the ‘CDO’, and the expectations and ambitions of organisations. Most importantly, it will place the role of the CDO into the context of a c-suite player for organisations that wish to recover quickly and with long-term stability from the current global economic downturn. New coverage includes: - the evolution of the CDO role, what those changes mean for organisations and individuals, and what the future might hold - a focus on ethics, the data revolution and all the areas that help readers take their first steps on the data journey - new conversations and experiences from an alumni of data leaders compiled over the past three years - new chapters and reflections on being a third generation CDO and on working across a broad spectrum of organisations who are all on different parts of their data journey. Written in a highly accessible and practical manner, The Chief Data Officer’s Playbook, Second Edition brings the most up-to-date guidance to CDO’s who wish to understand their position better; to those aspiring to become CDO’s; to those who might be recruiting a CDO and to recruiters to understand an organisation seeking a CDO and the CDO landscape. |
| dama dmbok data management body of knowledge: The Chief Data Officer Management Handbook Martin Treder, 2020-10-03 There is no denying that the 21st century is data driven, with many digital industries relying on careful collection and analysis of mass volumes of information. A Chief Data Officer (CDO) at a company is the leader of this process, making the position an often daunting one. The Chief Data Officer Management Handbook is here to help. With this book, author Martin Treder advises CDOs on how to be better prepared for their swath of responsibilities, how to develop a more sustainable approach, and how to avoid the typical pitfalls. Based on positive and negative experiences shared by current CDOs, The Chief Data Officer Management Handbook guides you in designing the ideal structure of a data office, implementing it, and getting the right people on board. Important topics such as the data supply chain, data strategy, and data governance are thoughtfully covered by Treder. As a CDO it is important to use your position effectively with your entire team. The Chief Data Officer Management Handbook allows all employees to take ownership in data collaboration. Data is the foundation of present and future tech innovations, and you could be the leader that makes the next big impact. What You Will Learn Apply important elements of effective data management Gain a comprehensive overview of all areas of data (which are often managed independently Work with the data supply chain, from data acquisition to its usage, a review of all relevant stakeholders, data strategy, and data governance Who This Book is For CDOs, data executives, data advisors, and all professionals looking to understand about how a data office functions in an organization. |
| dama dmbok data management body of knowledge: Executing Data Quality Projects Danette McGilvray, 2021-05-27 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 |
| dama dmbok data management body of knowledge: The Data and Analytics Playbook Lowell Fryman, Gregory Lampshire, Dan Meers, 2016-08-12 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 |
| dama dmbok data management body of knowledge: Monetizing Data Management Peter Aiken, Juanita Billings, 2013-10 What’s the Return on Investment (ROI) on data management? Sound like an impossible question to answer? Not if you read this book and learn the value-added approach to managing enterprise resources and assets. This book defines the five interrelated best practices that comprise data management, and shows you how by example to successfully communicate data management ROI to senior management. The 17 cases we share will help you to identify opportunities to introduce data management into the strategic conversations that occur in the C-suite. You will gain a new perspective regarding the stewardship of your data assets and insulate your operations from the chaos, losses and risks that result from traditional approaches to technological projects. And you will learn how to protect yourself from legal challenges resulting from outsourced information technology projects gone badly due to incorrect project sequencing and focus. With the emerging acceptance and adoption of revised performance standards, your organization will be better prepared to face the coming big data deluge! The book contains four chapters: • Chapter 1 gives a somewhat unique perspective to the practice of leveraging data. We describe the motivations and delineate the specific challenges preventing most organizations from making substantial progress in this area. • Chapter 2 presents 11 cases where leveraging data has produced positive financial results that can be presented in language of immediate interest to C-level executives. To the degree possible, we have quantified the effect that data management has had in terms that will be meaningful to them also. • Chapter 3 describes five instances taken from the authors' experiences with various governmental defense departments. The lessons in this section however can be equally applied to many non-profit and non-defense governmental organizations. • Chapter 4 speaks specifically to the interaction of data management practices, in terms of both information technology projects and legal responsibilities. Reading it can help your organization avoid a number of perils, stay out of court and better vet contractors, experts and other helpers who play a role in organization information technology development. From John Bottega Foreword: Data is the new currency. Yes, an expression that is being used quite a bit of late, but it is very relevant in discussing the importance of data and the methodologies by which we manage it. And like any currency, how we manage it determines its true value. Like any currency, it can be managed wisely, or it can be managed foolishly. It can be put to good use, or it can be squandered away. The question is – what factors determine the path that we take? How do we properly manage this asset and realize its full value and potential? In Monetizing Data Management, Peter and Juanita explore the question of how to understand and place tangible value on data and data management. They explore this question through a series of examples and real-world use cases to exemplify how the true value of data can be realized. They show how bringing together business and technology, and applying a data-centric forensic approach can turn massive amounts of data into the tools needed to improve business processes, reduce costs, and better serve the customer. Data monetization is not about turning data into money. Instead, it’s about taking information and turning it into opportunity. It’s about the need to understand the real meaning of data in order to extract value from it. And it’s about achieving this objective through a partnership with business and technology. In Monetizing Data Management, the authors demonstrate how true value can be realized from our data through improved data centric approaches. |
| dama dmbok data management body of knowledge: Get Governed Morgan Templar, 2017-09-13 Get Governed is the textbook for data governance professionals. Templar delivers complex information in an approachable style while offering the most accurate and easy to comprehend path toward proper and complete Data Governance for businesses of all sizes and types. Templar quickly conveys why governance matters and how it benefits your organization. No other book on Data Governance provides such a clear roadmap to success while keeping you awake and entertained with stories of how Data Governance has made a difference in the lives of customers and employees. With millions of data points changing every day, there is no time to waste. It is time to Get Governed! ADVANCED PRAISE: Because data has quietly and quickly reached a critical mass of volume and complexity, the immense opportunities we seek with it can only be achieved when matched with a process of refining it to the few elements among the many that deserve the title 'asset.' Morgan is sharing how data presents endless opportunities once the right structure, leadership, conversations and cultural shift begin to take place. Whether you picked up this book for curiosity or because you are now responsible for delivering Data Governance to an organization, Get Governed is a well-composed guide that will change the way you think about the problem. Morgan thoughtfully lays out the reasons for Data Governance, the setup, the buy-in, the proof-points and the successes and failures to learn from. Morgan takes you on this journey in such an approachable manner that average people and experienced data management professionals alike can all reap the benefits of her experience and knowledge. Data Governance can be broken down into driving value for three core objectives: Analytics and Insights, Operational Excellence and Compliance & Reporting. Use cases related to each define a reason for why data must be trusted and the means for how it must be governed to deliver trust. This next era of business is only going to be successful by embracing data governance and the importance of the trusted insight you will gain. - Marie Klok Crump, COO, Datum Healthcare organizations are just starting to realize the potential value of the data they are sitting on, and 'Get Governed' explains both the why and the how to help organizations find the hidden value of those data assets. Whether you're just getting started, or have been in information management for years, Get Governed provides a practical, down-to-earth guide to get your organization on the right path to effective data governance. - Glen Schuster, Founder and Principal, Skrymir Data Strategies; Former CTO of Centene Corporation. This book provides a unique perspective on the missing link in many organizations' data strategies - Governance. Governance is not just about control and decision making; it's how you enable the effective use of Data and Information to drive value and align it to the stakeholders which companies serve. As data consumption continues to grow exponentially, putting in place the right governance processes is critical. 'Get Governed' helps put some context and structure around these efforts. - Bill Fandrich, SVP and CIO Blue Cross Blue Shield of Michigan. |
| dama dmbok data management body of knowledge: Principles of Data Management Keith Gordon, 2013-11-18 Data is a valuable corporate asset and its effective management can be vital to an organisation’s success. This professional guide covers all the key areas of data management, including database development and corporate data modelling. It is business-focused, providing the knowledge and techniques required to successfully implement the data management function. This new edition covers web technology and its relation to databases and includes material on the management of master data. |
| dama dmbok data management body of knowledge: The Data Governance Guidebook and Playbook Kimberly Wienzierl, 2021-10-10 Implement and perform data governance on any scale using the book's flexible and proven data governance framework. This book is a culmination of decades of experience and trial and error implementations of data governance. There are many different ways to do data governance, so this is a consolidated framework that has been researched, developed, honed, piloted, and implemented at many different sizes of enterprises across many industries. Mold the book's flexible framework to jumpstart your data governance program. This book is a reference guide for Data Owners, Data Stewards, Data Custodians, Data Analysts, Application Developers, Database Administrators, Data Producers, and Data Consumers. Use it as a resource when you need to answer questions about data governance. It will guide you to successfully manage the creation, transformation, and usage of data owned by or in the care of your enterprise. |
| dama dmbok data management body of knowledge: The DAMA Guide to the Data Management Body of Knowledge (DAMA-DMBOK) Spanish Edition DAMA International, 2015-12-29 Escrito por más de 120 profesionistas en la gestión de datos, la guía DAMA de los fundamentos para la gestión de datos (DAMA-DMBOK) es la recopilación más impresionante jamás realizada de principios y mejores prácticas en la gestión de datos. Este libro proporciona a profesionales de IT, ejecutivos, trabajadores del conocimiento, educadores e investigadores de gestión de datos un método de manejo de datos para desarrollar su arquitectura de información. En comparación con los libros PMBOK o el BABOK, el libro DAMA-DMBOK proporciona información sobre: · Gobierno de datos · Gestión de Arquitectura de Datos · Desarrollo de datos · Gestión de Operaciones de base de datos · Gestión de la seguridad de datos · Gestión de datos maestros y de referencia · Gestión de almacenamiento de datos e inteligencia de negocios · Gestión de documentación y contenidos · Gestión de metadatos · Gestión de calidad de datos · Desarrollo profesional Como introducción oficial a la gestión de datos, los objetivos de la guía DAMA-DMBOK son: · Construir consensos para una visión general aplicable a las funciones de gestión de datos. · Proporcionar definiciones estandarizadas para funciones comúnmente utilizadas en la gestión de datos, resultados, roles y otras terminologías. · Documentar principios guiados para la gestión de datos. · Presentar una visión neutral de buenas prácticas comúnmente aceptadas, técnicas y métodos ampliamente adoptados, y alcances alternativos significantes. · Clarificar los alcances y límites de la gestión de datos. · Desempeñarse como guía de referencia para una mayor compresión para el lector Editores: Mark Mosley, Editor de desarrollo, Michel Brackett, Editor de producción, Susan Early, Asistente de editor, y Deborah Henderson, Patrocinador del proyecto. Prologo por John Zachman, Prefacio por John Schley (presidente internacional de DAMA) y Deborah Henderson (Presidenta de fundación DAMA, Vicepresidenta internacional de educación e investigación DAMA) y Epilogo por Michel Brackett. (Galardonado al Premio a la Trayectoria de DAMA Internacional). El DMBOK fue traducido al español por: Derly Almanza, Cinthia Carolina Sanchez Osorio, Karen Dawson, Ramón Vasquez, Juan Azcurra, Juan Diego Lorenzo, Fernado Giliberto, Sergio Tornati y Pablo Cigliuti. Prólogo por John Zachman: El libro es una recopilación exhaustiva de todos los temas y casos posibles que merecen consideración para iniciar y ejecutar u responsabilidades de gestión de datos en una empresa moderna. Es impresionante en su integralidad. No sólo identifica las metas y los objetivos de todos los temas de gestión de datos y las responsabilidades sino también sugiere de manera natural los participantes en la organización y los resultados finales que se deben esperar. La publicación comenzó como una recopilación trascendente muy necesaria de artículos y hechos sustantivos acerca del poco entendimiento del tema de la gestión de datos organizada por algunas personas de la sección Chicago de DAMA. Este material fue único en su momento por la carencia de información relacionada a este tema. Ha progresado hasta convertirse en un manual facultativo que merece un lugar en cualquier anaquel de gestión de datos. Hay una gran cantidad de información para el principiante de datos, pero también es de gran valor para el experto utilizándolo como una lista de comprobación y validación de sus conocimientos y responsabilidades para asegurar que nada se le ha olvidado. Es impresionante su amplitud y exhaustividad. La guía DAMA-DMBOK merece un lugar en cada estantería de libros de profesionistas de gestión de datos y para un gerente general servirá como guía para establecer expectativas y para asignar responsabilidades para la gestión y la práctica de lo que se ha convertido en el recurso más crítico de la empresa que ha progresado en la era de la información: DATOS! |
| dama dmbok data management body of knowledge: Big Data Viktor Mayer-Schönberger, Kenneth Cukier, 2013 A exploration of the latest trend in technology and the impact it will have on the economy, science, and society at large. |
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The Dama Guide to the Data Management Body of Knowledge (Japanese edition) Dama International,2009-04-01 Written by over 120 data management practitioners, the DAMA Guide …
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The Dama Guide to the Data Management Body of Knowledge (Japanese edition) Dama International,2009-04-01 Written by over 120 data management practitioners, the DAMA Guide …
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Dama Dmbok Data Management Body Of Knowledge
The Dama Guide to the Data Management Body of Knowledge (Japanese edition) Dama International,2009-04-01 Written by over 120 data management practitioners, the DAMA Guide …
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The Dama Guide to the Data Management Body of Knowledge (Japanese edition) Dama International,2009-04-01 Written by over 120 data management practitioners, the DAMA Guide …
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The Dama Guide to the Data Management Body of Knowledge (Japanese edition) Dama International,2009-04-01 Written by over 120 data management practitioners, the DAMA Guide …
Dama Dmbok Data Management Body Of Knowledge (book)
The Dama Guide to the Data Management Body of Knowledge (Japanese edition) Dama International,2009-04-01 Written by over 120 data management practitioners, the DAMA Guide …
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The Dama Guide to the Data Management Body of Knowledge (Japanese edition) Dama International,2009-04-01 Written by over 120 data management practitioners, the DAMA Guide …
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The Dama Guide to the Data Management Body of Knowledge (Japanese edition) Dama International,2009-04-01 Written by over 120 data management practitioners, the DAMA Guide …
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The Dama Guide to the Data Management Body of Knowledge (Japanese edition) Dama International,2009-04-01 Written by over 120 data management practitioners, the DAMA Guide …
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The Dama Guide to the Data Management Body of Knowledge (Japanese edition) Dama International,2009-04-01 Written by over 120 data management practitioners the DAMA Guide …
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The Dama Guide to the Data Management Body of Knowledge (Japanese edition) Dama International,2009-04-01 Written by over 120 data management practitioners, the DAMA Guide …
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The Dama Guide to the Data Management Body of Knowledge (Japanese edition) Dama International,2009-04-01 Written by over 120 data management practitioners the DAMA Guide …
Dama Dmbok Data Management Body Of Knowledge
The Dama Guide to the Data Management Body of Knowledge (Japanese edition) Dama International,2009-04-01 Written by over 120 data management practitioners, the DAMA Guide …
Dama Dmbok Data Management Body Of Knowledge (PDF)
The Dama Guide to the Data Management Body of Knowledge (Japanese edition) Dama International,2009-04-01 Written by over 120 data management practitioners, the DAMA Guide …
