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Author: Dama International
Publisher:
ISBN: 9781634622349
Category : Database management
Languages : en
Pages : 628
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Book Description
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.
Author: Dama International
Publisher:
ISBN: 9781634622349
Category : Database management
Languages : en
Pages : 628
Get Book Here
Book Description
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.
Author: Mark Mosley
Publisher:
ISBN: 9781935504023
Category : Business & Economics
Languages : en
Pages : 0
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Book Description
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.
Author: Piethein Strengholt
Publisher: "O'Reilly Media, Inc."
ISBN: 1492054739
Category : Computers
Languages : en
Pages : 372
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Book Description
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
Author: Laura Sebastian-Coleman
Publisher: Technics Publications
ISBN: 1634623770
Category : Computers
Languages : en
Pages : 123
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Book Description
An Executive Guide to Data Management
Author: John Ladley
Publisher: Academic Press
ISBN: 0128158328
Category : Technology & Engineering
Languages : en
Pages : 352
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Book Description
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
Author: David Plotkin
Publisher: Newnes
ISBN: 0124104452
Category : Computers
Languages : en
Pages : 251
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Book Description
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
Author: Laura Sebastian-Coleman
Publisher: Newnes
ISBN: 0123977541
Category : Computers
Languages : en
Pages : 404
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Book Description
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
Author: Robert S. Seiner
Publisher: Technics Publications
ISBN: 1634620453
Category : Computers
Languages : en
Pages : 147
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Book Description
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.
Author: Danette McGilvray
Publisher: Elsevier
ISBN: 0080558399
Category : Computers
Languages : en
Pages : 353
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Book Description
Information is currency. Recent 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. In this important and timely new book, Danette McGilvray presents her "Ten Steps approach to information quality, a proven method for both understanding and creating information quality in the enterprise. Her trademarked approach—in which she has trained Fortune 500 clients and hundreds of workshop attendees—applies to all types of data and to all types of organizations.* Includes numerous templates, detailed examples, and practical advice for executing every step of the "Ten Steps approach.* 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 planning and information-gathering templates featured in the text, quick summaries of key ideas from the Ten Step methodology, and other tools and information available online.
Author: Bas van Gils
Publisher: Van Haren
ISBN: 9401805555
Category : Architecture
Languages : en
Pages : 355
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Book Description
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.
