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Multi Domain Master Data Management

Multi Domain Master Data Management Author Mark Allen
ISBN-10 9780128011478
Release 2015-03-21
Pages 244
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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.



Master Data Management in Practice

Master Data Management in Practice Author Dalton Cervo
ISBN-10 9780470910559
Release 2011-07-05
Pages 247
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Dalton and Mark explain how MDM does much more than just bring data together-it provides a set of processes, services, and policies that bring people together in a cross-functional and collaborative approach to enterprise data management, where people, empowered by high quality data and enabled by technology, can optimize business processes for superior business performance."--Jim Harris, independent consultant, speaker, and freelance writer, as well as the Blogger-in-Chief at Ob



Enterprise Master Data Management

Enterprise Master Data Management Author Allen Dreibelbis
ISBN-10 9780132704274
Release 2008-06-05
Pages 656
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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



Requirements for an Mdm Solution

Requirements for an Mdm Solution Author Vicki McCracken
ISBN-10 1533555176
Release 2016-11-09
Pages 46
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Working on Requirements for a Master Data Management solution and looking for thoughts on how to approach the requirements? The focus of this guide is to highlight a proven approach for requirements gathering and documentation for Master Data Management solutions. Requirements gathering and documentation activities are similar, regardless of the type of project. What differs is the approach, the emphasis of specific activities, and the content of work products. MDM projects do not come along often; this guide can serve as a roadmap for how to approach requirements for an MDM solution. The guide begins with a brief overview of Master Data Management. The guide then steps through the requirements activities and work products for each Solution Development Lifecycle phase. The requirements work products are described, along with an example of each work product. Below is a summary of the phases and primary work products produced: - Alignment: where the Business Requirements, including solution Features are defined - Solution Scoping: where the Solution Requirements, including Information Requirements, Business Rules, and Epics (Functions), are defined - Functional Requirements: where a given Epic (Function) is elaborated on, including inputs, outputs, data updates, business rules, an activity diagram, and associated User Stories - User Stories: where Acceptance Criteria is defined Keys to success are identified for the various phases. In addition, for Solution Scoping, there is a section which focuses on how to approach, plan, and track Solution Scoping. Finally, there is an overview of Change Management and Traceability. The Guide contains 44 illustrations, 32 of which are examples of work products. It includes many visual work products, which help to ensure a consistent understanding of the solution. The guide assumes some familiarity with requirements gathering techniques and work products; it does not focus on techniques. The guide demonstrates how to structure the various requirements activities, to successfully gather and document requirements for an MDM solution. The guide also does not focus on formulating an MDM Business Case, MDM Architecture, or technical system requirements. The guide is intended to assist requirements analysts in formulating an approach for how to gather and document requirements for a Master Data Management solution.



Managing Data in Motion

Managing Data in Motion Author April Reeve
ISBN-10 9780123977915
Release 2013-02-26
Pages 204
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Managing Data in Motion describes techniques that have been developed for significantly reducing the complexity of managing system interfaces and enabling scalable architectures. Author April Reeve brings over two decades of experience to present a vendor-neutral approach to moving data between computing environments and systems. Readers will learn the techniques, technologies, and best practices for managing the passage of data between computer systems and integrating disparate data together in an enterprise environment. The average enterprise's computing environment is comprised of hundreds to thousands computer systems that have been built, purchased, and acquired over time. The data from these various systems needs to be integrated for reporting and analysis, shared for business transaction processing, and converted from one format to another when old systems are replaced and new systems are acquired. The management of the "data in motion" in organizations is rapidly becoming one of the biggest concerns for business and IT management. Data warehousing and conversion, real-time data integration, and cloud and "big data" applications are just a few of the challenges facing organizations and businesses today. Managing Data in Motion tackles these and other topics in a style easily understood by business and IT managers as well as programmers and architects. Presents a vendor-neutral overview of the different technologies and techniques for moving data between computer systems including the emerging solutions for unstructured as well as structured data types Explains, in non-technical terms, the architecture and components required to perform data integration Describes how to reduce the complexity of managing system interfaces and enable a scalable data architecture that can handle the dimensions of "Big Data"



SAP Master Data Governance

SAP Master Data Governance Author Homiar Kalwachwala
ISBN-10 1493214330
Release 2017
Pages 627
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SAP master data governance - overview -- Data modeling -- Overview -- Data migration



Master Data Management Mdm

Master Data Management Mdm Author Gerard Blokdyk
ISBN-10 1978261608
Release 2017-10-14
Pages 124
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What prevents me from making the changes I know will make me a more effective Master Data Management MDM leader? How do we Improve Master Data Management MDM service perception, and satisfaction? How will the Master Data Management MDM team and the organization measure complete success of Master Data Management MDM? How does the organization define, manage, and improve its Master Data Management MDM processes? Has the direction changed at all during the course of Master Data Management MDM? If so, when did it change and why? Defining, designing, creating, and implementing a process to solve a business challenge or meet a business objective is the most valuable role... In EVERY company, organization and department. Unless you are talking a one-time, single-use project within a business, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' For more than twenty years, The Art of Service's Self-Assessments empower people who can do just that - whether their title is marketer, entrepreneur, manager, salesperson, consultant, business process manager, executive assistant, IT Manager, CxO etc... - they are the people who rule the future. They are people who watch the process as it happens, and ask the right questions to make the process work better. This book is for managers, advisors, consultants, specialists, professionals and anyone interested in Master Data Management MDM assessment. All the tools you need to an in-depth Master Data Management MDM Self-Assessment. Featuring new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Master Data Management MDM improvements can be made. In using the questions you will be better able to: - diagnose Master Data Management MDM projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Master Data Management MDM and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Master Data Management MDM Scorecard, you will develop a clear picture of which Master Data Management MDM areas need attention. Included with your purchase of the book is the Master Data Management MDM Self-Assessment downloadable resource, which contains all questions and Self-Assessment areas of this book in a ready to use Excel dashboard, including the self-assessment, graphic insights, and project planning automation - all with examples to get you started with the assessment right away. Access instructions can be found in the book. You are free to use the Self-Assessment contents in your presentations and materials for customers without asking us - we are here to help.



MASTER DATA MANAGEMENT AND DATA GOVERNANCE 2 E

MASTER DATA MANAGEMENT AND DATA GOVERNANCE  2 E Author Alex Berson
ISBN-10 9780071744591
Release 2010-12-06
Pages 512
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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



Master Data Management

Master Data Management Author David Loshin
ISBN-10 0080921213
Release 2010-07-28
Pages 304
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The key to a successful MDM initiative isn’t technology or methods, it’s people: the stakeholders in the organization and their complex ownership of the data that the initiative will affect. Master Data Management equips you with a deeply practical, business-focused way of thinking about MDM—an understanding that will greatly enhance your ability to communicate with stakeholders and win their support. Moreover, it will help you deserve their support: you’ll master all the details involved in planning and executing an MDM project that leads to measurable improvements in business productivity and effectiveness. * Presents a comprehensive roadmap that you can adapt to any MDM project. * Emphasizes the critical goal of maintaining and improving data quality. * Provides guidelines for determining which data to “master. * Examines special issues relating to master data metadata. * Considers a range of MDM architectural styles. * Covers the synchronization of master data across the application infrastructure.



Big Data Governance

Big Data Governance Author Sunil Soares
ISBN-10 1583473777
Release 2012-11-01
Pages 342
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Written by a leading expert in the field, this account focuses on the convergence of two major trends in information management—big data and information governance—by taking a strategic approach oriented around business cases and industry imperatives. With the advent of new technologies, enterprises are expanding and handling very large volumes of data; this book, nontechnical in nature and geared toward business audiences, encourages the practice of establishing appropriate governance over big data initiatives and addresses how to manage and govern big data, highlighting the relevant processes, procedures, and policies. It teaches readers to understand how big data fits within an overall information governance program; quantify the business value of big data; apply information governance concepts such as stewardship, metadata, and organization structures to big data; appreciate the wide-ranging business benefits for various industries and job functions; sell the value of big data governance to businesses; and establish step-by-step processes to implement big data governance.



Beyond Big Data

Beyond Big Data Author Martin Oberhofer
ISBN-10 9780133509816
Release 2014-10-17
Pages 272
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Drive Powerful Business Value by Extending MDM to Social, Mobile, Local, and Transactional Data Enterprises have long relied on Master Data Management (MDM) to improve customer-related processes. But MDM was designed primarily for structured data. Today, crucial information is increasingly captured in unstructured, transactional, and social formats: from tweets and Facebook posts to call center transcripts. Even with tools like Hadoop, extracting usable insight is difficult—often, because it’s so difficult to integrate new and legacy data sources. In Beyond Big Data, five of IBM’s leading data management experts introduce powerful new ways to integrate social, mobile, location, and traditional data. Drawing on pioneering experience with IBM’s enterprise customers, they show how Social MDM can help you deepen relationships, improve prospect targeting, and fully engage customers through mobile channels. Business leaders and practitioners will discover powerful new ways to combine social and master data to improve performance and uncover new opportunities. Architects and other technical leaders will find a complete reference architecture, in-depth coverage of relevant technologies and use cases, and domain-specific best practices for their own projects. Coverage Includes How Social MDM extends fundamental MDM concepts and techniques Architecting Social MDM: components, functions, layers, and interactions Identifying high value relationships: person to product and person to organization Mapping Social MDM architecture to specific products and technologies Using Social MDM to create more compelling customer experiences Accelerating your transition to highly-targeted, contextual marketing Incorporating mobile data to improve employee productivity Avoiding privacy and ethical pitfalls throughout your ecosystem Previewing Semantic MDM and other emerging trends



Customer Data Integration

Customer Data Integration Author Jill Dyché
ISBN-10 9781118046470
Release 2011-01-31
Pages 320
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"Customers are the heart of any business. But we can't succeed if we develop only one talk addressed to the 'average customer.' Instead we must know each customer and build our individual engagements with that knowledge. If Customer Relationship Management (CRM) is going to work, it calls for skills in Customer Data Integration (CDI). This is the best book that I have seen on the subject. Jill Dyché is to be complimented for her thoroughness in interviewing executives and presenting CDI." -Philip Kotler, S. C. Johnson Distinguished Professor of International Marketing Kellogg School of Management, Northwestern University "In this world of killer competition, hanging on to existing customers is critical to survival. Jill Dyché's new book makes that job a lot easier than it has been." -Jack Trout, author, Differentiate or Die "Jill and Evan have not only written the definitive work on Customer Data Integration, they've made the business case for it. This book offers sound advice to business people in search of innovative ways to bring data together about customers-their most important asset-while at the same time giving IT some practical tips for implementing CDI and MDM the right way." -Wayne Eckerson, The Data Warehousing Institute author of Performance Dashboards: Measuring, Monitoring, and Managing Your Business Whatever business you're in, you're ultimately in the customer business. No matter what your product, customers pay the bills. But the strategic importance of customer relationships hasn't brought companies much closer to a single, authoritative view of their customers. Written from both business and technicalperspectives, Customer Data Integration shows companies how to deliver an accurate, holistic, and long-term understanding of their customers through CDI.



Aligning MDM and BPM for Master Data Governance Stewardship and Enterprise Processes

Aligning MDM and BPM for Master Data Governance  Stewardship  and Enterprise Processes Author Chuck Ballard
ISBN-10 9780738437743
Release 2013-03-08
Pages 212
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An enterprise can gain differentiating value by aligning its master data management (MDM) and business process management (BPM) projects. This way, organizations can optimize their business performance through agile processes that empower decision makers with the trusted, single version of information. Many companies deploy MDM strategies as assurances that enterprise master data can be trusted and used in the business processes. IBM® InfoSphere® Master Data Management creates trusted views of data assets and elevates the effectiveness of an organization's most important business processes and applications. This IBM Redbooks® publication provides an overview of MDM and BPM. It examines how you can align them to enable trusted and accurate information to be used by business processes to optimize business performance and bring more agility to data stewardship. It also provides beginning guidance on these patterns and where cross-training efforts might focus. This book is written for MDM or BPM architects and MDM and BPM architects. By reading this book, MDM or BPM architects can understand how to scope joint projects or to provide reasonable estimates of the effort. BPM developers (or MDM developers with BPM training) can learn how to design and build MDM creation and consumption use cases by using the MDM Toolkit for BPM. They can also learn how to import data governance samples and extend them to enable collaborative stewardship of master data.



Building 360 Degree Information Applications

Building 360 Degree Information Applications Author Whei-Jen Chen
ISBN-10 9780738439921
Release 2014-10-01
Pages 240
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Today's businesses, applications, social media, and online transactions generate more data than ever before. This data can be explored and analyzed to provide tremendous business value. IBM® WatsonTM Explorer and IBM InfoSphere® Master Data Management (InfoSphere MDM) enable organizations to simultaneously explore and derive insights from enterprise data that was traditionally stored in "silos" in enterprise applications, different data repositories, and in different data formats. This IBM Redbooks® publication provides information about Watson Explorer 9.0, InfoSphere MDM, and IBM InfoSphere MDM Probabilistic Matching Engine for InfoSphere BigInsightsTM (PME for BigInsights). It gives you an overview, describes the architecture, and presents use cases that you can use to accomplish the following tasks: Understand the core capabilities of Watson Explorer, InfoSphere MDM, and PME for BigInsights. Realize the full potential of Watson Explorer applications. Describe the integration and value of the combination of Watson Explorer and InfoSphere MDM. Build a 360-degree information application. Learn by example by following hands-on lab scenarios. /ul>



Non Invasive Data Governance

Non Invasive Data Governance Author Robert S. Seiner
ISBN-10 9781634620451
Release 2014-09-01
Pages 148
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Data-governance programs focus on authority and accountability for the management of data as a valued organizational asset. Data Governance should not be about command-and-control, yet at times could become invasive or threatening to the work, people and culture of an organization. Non-Invasive Data Governance™ focuses on formalizing existing accountability for the management of data and improving formal communications, protection, and quality efforts through effective stewarding of data resources. Non-Invasive Data Governance will provide you with a complete set of tools to help you deliver a successful data governance program. Learn how: • Steward responsibilities can be identified and recognized, formalized, and engaged according to their existing responsibility rather than being assigned or handed to people as more work. • Governance of information can be applied to existing policies, standard operating procedures, practices, and methodologies, rather than being introduced or emphasized as new processes or methods. • Governance of information can support all data integration, risk management, business intelligence and master data management activities rather than imposing inconsistent rigor to these initiatives. • A practical and non-threatening approach can be applied to governing information and promoting stewardship of data as a cross-organization asset. • Best practices and key concepts of this non-threatening approach can be communicated effectively to leverage strengths and address opportunities to improve.



Data Governance

Data Governance Author John Ladley
ISBN-10 9780124158290
Release 2012
Pages 236
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This book is for any manager or team leader that has the green light to implement a data governance program What you will find in this book is an overview of why data governance is needed, how to design, initiate, and execute a program and how to keep the program sustainable.



Data Governance Tools

Data Governance Tools Author Sunil Soares
ISBN-10 1583478442
Release 2015-02-01
Pages 368
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Comprehensively covers evaluation criteria for and capabilities of the software tools available for implementing a data governance program Data governance programs often start off using programs such as Microsoft Excel and Microsoft SharePoint to document and share data governance artifacts. But these tools often lack critical functionality. Meanwhile, vendors have matured their data governance offerings to the extent that today's organizations need to consider tools as a critical component of their data governance programs. In this book, data governance expert Sunil Soares reviews the Enterprise Data Management (EDM) reference architecture and discusses key data governance tasks that can be automated by tools for business glossaries, metadata management, data profiling, data quality management, master data management, reference data management, and information policy management. Subsequent sections describe the integration points between EDM tools and data governance and examine how governance tools interact with big data technologies, including Hadoop, NoSQL, stream computing, and text analytics. The final section of the book discusses evaluation criteria for data governance tools and provides an overview of key vendor platforms, including ASG, Collibra, Global IDs, IBM, Informatica, Orchestra Networks, SAP, and Talend.