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| erp master data management: 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 |
| erp master data management: Master Data Management and Customer Data Integration for a Global Enterprise Alex Berson, Larry Dubov, 2007-05-22 Transform your business into a customer-centric enterprise Gain a complete and timely understanding of your customers using MDM-CDI and the real-world information contained in this comprehensive volume. Master Data Management and Customer Data Integration for a Global Enterprise explains how to grow revenue, reduce administrative costs, and improve client retention by adopting a customer-focused business framework. Learn to build and use customer hubs and associated technologies, secure and protect confidential corporate and customer information, provide personalized services, and set up an effective data governance team. You'll also get full details on regulatory compliance and the latest pre-packaged MDM-CDI software solutions. Design and implement a dynamic MDM-CDI architecture that fits the needs of your business Implement MDM-CDI holistically as an integrated multi-disciplinary set of technologies, services, and processes Improve solution agility and flexibility using SOA and Web services Recognize customers and their relationships with the enterprise across channels and lines of business Ensure compliance with local, state, federal, and international regulations Deploy network, perimeter, platform, application, data, and user-level security Protect against identity and data theft, worm infection, and phishing and pharming scams Create an Enterprise Information Governance Group Perform development, QA, and business acceptance testing and data verification |
| erp master data management: Master Data Management David Loshin, 2010-07-28 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 |
| erp master data management: SAP Master Data Governance Homiar Kalwachwala, Sandeep Chahal, Santhosh Cheekoti, Antony Isacc, Rajani Khambhampati, Vikas Lodha, Syama Srinivasan, David Quirk, 2019 Ready to improve the handling of your master data? Walk through implementing, configuring, and using SAP Master Data Governance (SAP MDG)! Whether your organization requires custom applications or works with out-of-the-box central governance, consolidation, and mass processing, you'll find detailed instructions for every step. From data, process, and UI modeling to data replication, master your data! Highlights include: 1) Deployment 2) Data modeling 3) Process modeling 4) Data quality 5) Data replication 6) Data migration 7) Consolidation 8) Operations 9) Mass processing 10) Integrations 11) Extensions 12) Analytics |
| erp master data management: 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 |
| erp master data management: Smarter Modeling of IBM InfoSphere Master Data Management Solutions Jan-Bernd Bracht, Joerg Rehr, Markus Siebert, Rouven Thimm, IBM Redbooks, 2012-08-09 This IBM® Redbooks® publication presents a development approach for master data management projects, and in particular, those projects based on IBM InfoSphere® MDM Server. The target audience for this book includes Enterprise Architects, Information, Integration and Solution Architects and Designers, Developers, and Product Managers. Master data management combines a set of processes and tools that defines and manages the non-transactional data entities of an organization. Master data management can provide processes for collecting, consolidating, persisting, and distributing this data throughout an organization. IBM InfoSphere Master Data Management Server creates trusted views of master data that can improve applications and business processes. You can use it to gain control over business information by managing and maintaining a complete and accurate view of master data. You also can use InfoSphere MDM Server to extract maximum value from master data by centralizing multiple data domains. InfoSphere MDM Server provides a comprehensive set of prebuilt business services that support a full range of master data management functionality. |
| erp master data management: MASTER DATA MANAGEMENT AND DATA GOVERNANCE, 2/E Alex Berson, Larry Dubov, 2010-11-09 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 |
| erp master data management: Enterprise Data Governance Pierre Bonnet, 2013-03-04 In an increasingly digital economy, mastering the quality of data is an increasingly vital yet still, in most organizations, a considerable task. The necessity of better governance and reinforcement of international rules and regulatory or oversight structures (Sarbanes Oxley, Basel II, Solvency II, IAS-IFRS, etc.) imposes on enterprises the need for greater transparency and better traceability of their data. All the stakeholders in a company have a role to play and great benefit to derive from the overall goals here, but will invariably turn towards their IT department in search of the answers. However, the majority of IT systems that have been developed within businesses are overly complex, badly adapted, and in many cases obsolete; these systems have often become a source of data or process fragility for the business. It is in this context that the management of ‘reference and master data’ or Master Data Management (MDM) and semantic modeling can intervene in order to straighten out the management of data in a forward-looking and sustainable manner. This book shows how company executives and IT managers can take these new challenges, as well as the advantages of using reference and master data management, into account in answering questions such as: Which data governance functions are available? How can IT be better aligned with business regulations? What is the return on investment? How can we assess intangible IT assets and data? What are the principles of semantic modeling? What is the MDM technical architecture? In these ways they will be better able to deliver on their responsibilities to their organizations, and position them for growth and robust data management and integrity in the future. |
| erp master data management: Aligning MDM and BPM for Master Data Governance, Stewardship, and Enterprise Processes Chuck Ballard, Trey Anderson, Dr. Lawrence Dubov, Alex Eastman, Jay Limburn, Umasuthan Ramakrishnan, IBM Redbooks, 2013-03-08 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. |
| erp master data management: Multi-Domain Master Data Management Mark Allen, Dalton Cervo, 2015-03-21 Multi-Domain Master Data Management delivers practical guidance and specific instruction to help guide planners and practitioners through the challenges of a multi-domain master data management (MDM) implementation. Authors Mark Allen and Dalton Cervo bring their expertise to you in the only reference you need to help your organization take master data management to the next level by incorporating it across multiple domains. Written in a business friendly style with sufficient program planning guidance, this book covers a comprehensive set of topics and advanced strategies centered on the key MDM disciplines of Data Governance, Data Stewardship, Data Quality Management, Metadata Management, and Data Integration. - Provides a logical order toward planning, implementation, and ongoing management of multi-domain MDM from a program manager and data steward perspective. - Provides detailed guidance, examples and illustrations for MDM practitioners to apply these insights to their strategies, plans, and processes. - Covers advanced MDM strategy and instruction aimed at improving data quality management, lowering data maintenance costs, and reducing corporate risks by applying consistent enterprise-wide practices for the management and control of master data. |
| erp master data management: Master Data Management for SaaS Applications Whei-Jen Chen, Bhavani Eshwar, Ramya Rajendiran, Shettigar Srinivas, Manjunath B Subramanian, Bharathi Venkatasubramanian, IBM Redbooks, 2014-10-19 Enterprises today understand the value of employing a master data management (MDM) solution for managing and governing mission critical information assets. chief data officers and chief information officers drive MDM initiatives with IBM® InfoSphere® Master Data Management to improve business results and operational efficiencies, which can help to lower costs and to reduce the risk of using untrusted master information in business process. Cloud computing introduces new considerations where enterprise IT architectures are extended beyond the corporate networks into the cloud. Many enterprises are now adopting turnkey business applications offered as software as a service (SaaS) solutions, such as customer relationship management (CRM), payroll processing, human resource management, and many more. However, in the context of MDM solutions, many organizations perceive risks in having these solutions deployed on the cloud. In some cases, organization are concerned with the legal restrictions of deploying solutions on the cloud, whereas in other cases organizations have policies and strategies in force that limit solution deployment on the cloud. Immaterial of what all the cases might be, industry trends point to a prediction that many extended enterprises will keep MDM solutions on premises and will want its integrations with SaaS applications, specifically customer and asset domains. This trend puts a key focus on an important component in the solution construct, that is, the cloud integration middleware and how it fits with hybrid cloud architectures that span on premises and cloud services. As this trend pans out, the on-premises MDM solution integration with SaaS applications will be the key pain point for the extended enterprise. This IBM Redbooks® publication provides guidance to chief data officers, chief information officers, MDM practitioners, integration architects, and others who are interested in the integration of IBM InfoSphere Master Data Management with SaaS applications. This book lays the background on how mastering and governance needs for SaaS applications is quite similar to what on-premises business applications would need. It draws the perspective for serving the on-premises application and the SaaS application with the same MDM hub. This book describes how IBM WebSphere® Cast Iron® Cloud Integration can serve as the de-facto cloud integration middleware to integrate the on-premises InfoSphere Master Data Management systems with any SaaS application by using Saleforce.com integration as an example. This book also covers aspects of handling bulk operations with IBM InfoSphere Information Server. After reading this book, you will have a good understanding about the considerations for on-premises InfoSphere Master Data Management integration with SaaS applications in general and Salesforce.com in particular. The MDM practitioners and integration architects will understand the deployable integrations patterns and, in general, will be able to effectively contribute to delivering strategies that involve building solutions in this area. Additionally, SaaS vendors and customers looking to build or implement SaaS solutions that might require trusted master information will be able to use this compilation to ensure that the right architecture is put together and adhered to as a set of standard integrations patterns with all the core building blocks is essential for the longevity of a solution in this space. |
| erp master data management: Effective Master Data Management with SAP NetWeaver MDM Andy N. Walker, Jagadeesh Ganapathy, 2009 This must-have reference for Master Data Management teaches you why and how to successfully integrate SAP NetWeaver MDM into your organization. Discover the key business reasons and benefits of implementing business partner master data processes with SAP NetWeaver MDM. You'll learn the business drivers for MDM, as well as the value of integrating with the Dun & Bradstreet services. From there, you'll travel through the complete process of planning for and implementing an MDM program. This is the complete guide for understanding what MDM is and what it can do for your business, teaching you how to develop the practical skills necessary to integrate SAP NetWeaver MDM into your systems landscape. Throughout the book, you'll find useful case studies and solution examples for implementing your MDM processes in SAP NetWeaver MDM 5.5 SP 06. |
| erp master data management: Enterprise Resource Planning and Supply Chain Management Karl E. Kurbel, 2013-08-23 This book is about running modern industrial enterprises with the help of information systems. Enterprise resource planning (ERP) is the core of business information processing. An ERP system is the backbone of most companies' information systems landscape. All major business processes are handled with the help of this system. Supply chain management (SCM) looks beyond the individual company, taking into account that enterprises are increasingly concentrating on their core competencies, leaving other activities to suppliers. With the growing dependency on the partners, effective supply chains have become as important for a company's success as efficient in-house processes. This book covers typical business processes and shows how these processes are implemented. Examples are presented using the leading systems on the market – SAP ERP and SAP SCM. In this way, the reader can understand how business processes are actually carried out in the real world. |
| erp master data management: Master Data Management in Practice Dalton Cervo, Mark Allen, 2011-05-25 In this book, authors Dalton Cervo and Mark Allen show you how to implement Master Data Management (MDM) within your business model to create a more quality controlled approach. Focusing on techniques that can improve data quality management, lower data maintenance costs, reduce corporate and compliance risks, and drive increased efficiency in customer data management practices, the book will guide you in successfully managing and maintaining your customer master data. You'll find the expert guidance you need, complete with tables, graphs, and charts, in planning, implementing, and managing MDM. |
| erp master data management: Managing Data in Motion April Reeve, 2013-02-26 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 |
| erp master data management: DAMA-DMBOK Dama International, 2017 Defining a set of guiding principles for data management and describing how these principles can be applied within data management functional areas; Providing a functional framework for the implementation of enterprise data management practices; including widely adopted practices, methods and techniques, functions, roles, deliverables and metrics; Establishing a common vocabulary for data management concepts and serving as the basis for best practices for data management professionals. DAMA-DMBOK2 provides data management and IT professionals, executives, knowledge workers, educators, and researchers with a framework to manage their data and mature their information infrastructure, based on these principles: Data is an asset with unique properties; The value of data can be and should be expressed in economic terms; Managing data means managing the quality of data; It takes metadata to manage data; It takes planning to manage data; Data management is cross-functional and requires a range of skills and expertise; Data management requires an enterprise perspective; Data management must account for a range of perspectives; Data management is data lifecycle management; Different types of data have different lifecycle requirements; Managing data includes managing risks associated with data; Data management requirements must drive information technology decisions; Effective data management requires leadership commitment. |
| erp master data management: 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 |
| erp master data management: Requirements for an Mdm Solution Vicki McCracken, 2016-11-09 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. |
| erp master data management: 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. |
| erp master data management: Customer Data Integration Jill Dyché, Evan Levy, 2011-01-31 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. |
| erp master data management: Managing Enterprise Resource Planning Adoption and Business Processes Chuck C.H. Law, 2019-04-03 The recent decades have witnessed many ERP failures attributable to a plethora of mistakes, and the author writes this book aiming to correct these malpractices concerning ERP adoption. The author presents an adoption methodology, called the Full Lifecycle ERP Adoption Reference (FLEAR) model, to promote holistic project management. Furthermore, from a holistic perspective, successful ERP adoption cannot be achieved in isolation of other business and organizational issues such as IT-business strategic alignment, IT governance, change management, and business process changes. Unlike many ERP books in the market which cover mostly technical deployment issues, this book also addresses the aforesaid business-related issues. Theoretical discussions are supported by extensive research, and practical experience drawn from North American and international contexts to benefit practitioners involved in international assignments. Thus, this book will benefit not only MIS personnel, but also non-technical business practitioners. It will also be a useful supplement for university-level MIS and business process management courses. |
| erp master data management: SAP Master Data Governance Bikram Dogra, David Quirk, Homiar Kalwachwala, Antony Isacc, Dilip Radhakrishnan, Syama Srinivasan, Sandeep Chahal, Santhosh Cheekoti, Rajani Khambhampati, Vikas Lodha, 2022 Manage your SAP S/4HANA and SAP ERP master data with this hands-on guide! Walk through implementing, configuring, and using SAP Master Data Governance, both on-premise and in the cloud! Whether your organization requires custom applications or works with out-of-the-box central governance, consolidation, and mass processing, you'll find detailed instructions for every step. From data modeling to data replication, this comprehensive guide will help you master your data!-- |
| erp master data management: Concepts in Enterprise Resource Planning Ellen F. Monk, Bret J. Wagner, 2013 Show your students how to master and maximize enterprise resource planning (ERP) software, which continues to become more critical in business today, with the latest edition of Monk/Wagner's successful CONCEPTS IN ENTERPRISE RESOURCE PLANNING, International Edition. Equip students to use ERP tools to increase growth and productivity as they learn how to effectively combine an organization's numerous functions into one comprehensive, integrated system. CONCEPTS IN ENTERPRISE RESOURCE PLANNING, 4E, International Edition reflects the latest trends and updates in ERP software while demonstrating how to make the most of this important technology.The authors introduce the basic functional areas of business and how they are related. The book demonstrates how information systems that are not effectively integrated fail to support business functions and business processes that extend across functional area boundaries. By contrast, students clearly see how integrated information systems help organizations improve business process and provide managers with accurate, consistent, and current data for making informed strategic decisions. All-new sidebar cases and real examples throughout this edition not only thoroughly introduce the practical aspects of enterprise resource planning, but also prepare readers for ongoing ERP success in business today and tomorrow. |
| erp master data management: Next-Generation Enterprise Security and Governance Mohiuddin Ahmed, Nour Moustafa, Abu Barkat, Paul Haskell-Dowland, 2022-04-19 The Internet is making our daily lives as digital as possible, and this new era is called the Internet of Everything (IoE). The key force behind the rapid growth of the Internet is the technological advancement of enterprises. The digital world we live in is facilitated by these enterprises’ advances and business intelligence. These enterprises need to deal with gazillions of bytes of data, and in today’s age of General Data Protection Regulation, enterprises are required to ensure privacy and security of large-scale data collections. However, the increased connectivity and devices used to facilitate IoE are continually creating more room for cybercriminals to find vulnerabilities in enterprise systems and flaws in their corporate governance. Ensuring cybersecurity and corporate governance for enterprises should not be an afterthought or present a huge challenge. In recent times, the complex diversity of cyber-attacks has been skyrocketing, and zero-day attacks, such as ransomware, botnet, and telecommunication attacks, are happening more frequently than before. New hacking strategies would easily bypass existing enterprise security and governance platforms using advanced, persistent threats. For example, in 2020, the Toll Group firm was exploited by a new crypto-attack family for violating its data privacy, where an advanced ransomware technique was launched to exploit the corporation and request a huge figure of monetary ransom. Even after applying rational governance hygiene, cybersecurity configuration and software updates are often overlooked when they are most needed to fight cyber-crime and ensure data privacy. Therefore, the threat landscape in the context of enterprises has become wider and far more challenging. There is a clear need for collaborative work throughout the entire value chain of this network. In this context, this book addresses the cybersecurity and cooperate governance challenges associated with enterprises, which will provide a bigger picture of the concepts, intelligent techniques, practices, and open research directions in this area. This book serves as a single source of reference for acquiring the knowledge on the technology, process, and people involved in next-generation privacy and security. |
| erp master data management: Building a Scalable Data Warehouse with Data Vault 2.0 Daniel Linstedt, Michael Olschimke, 2015-09-15 The Data Vault was invented by Dan Linstedt at the U.S. Department of Defense, and the standard has been successfully applied to data warehousing projects at organizations of different sizes, from small to large-size corporations. Due to its simplified design, which is adapted from nature, the Data Vault 2.0 standard helps prevent typical data warehousing failures. Building a Scalable Data Warehouse covers everything one needs to know to create a scalable data warehouse end to end, including a presentation of the Data Vault modeling technique, which provides the foundations to create a technical data warehouse layer. The book discusses how to build the data warehouse incrementally using the agile Data Vault 2.0 methodology. In addition, readers will learn how to create the input layer (the stage layer) and the presentation layer (data mart) of the Data Vault 2.0 architecture including implementation best practices. Drawing upon years of practical experience and using numerous examples and an easy to understand framework, Dan Linstedt and Michael Olschimke discuss: - How to load each layer using SQL Server Integration Services (SSIS), including automation of the Data Vault loading processes. - Important data warehouse technologies and practices. - Data Quality Services (DQS) and Master Data Services (MDS) in the context of the Data Vault architecture. - Provides a complete introduction to data warehousing, applications, and the business context so readers can get-up and running fast - Explains theoretical concepts and provides hands-on instruction on how to build and implement a data warehouse - Demystifies data vault modeling with beginning, intermediate, and advanced techniques - Discusses the advantages of the data vault approach over other techniques, also including the latest updates to Data Vault 2.0 and multiple improvements to Data Vault 1.0 |
| erp master data management: mySAP ERP For Dummies Andreas Vogel, Ian Kimbell, 2011-02-25 SAP is the world's leading provider of ERP software and services, with worldwide revenue in 2004 of $9.7 billion and a 57 percent market share among major business application providers; it is one of the world's largest software companies overall ERP is a flexible, open technology platform that helps businesses run more efficiently (and profitably) by providing integrated management of key operations and supply chains Written for IT professionals who find it hard to get through SAP's complex documentation, our book demonstrates how ERP can cut costs, provides a clear overview of how the ESA (enterprise service architecture) model affects ERP, and shows how to implement the new ERP in the real world Topics covered include reducing the cost of an existing IT backbone, using the new ERP to address a company's pain points and challenges, and proving the value of ERP through ROI (return on investment) and TCO (total cost of ownership) studies |
| erp master data management: Integrated Business Planning Robert Kepczynski, Raghav Jandhyala, Ganesh Sankaran, Alecsandra Dimofte, 2018-05-31 This book presents a comprehensive introduction to Integrated Business Planning (IBP), building on practitioner’s experience and showcasing the value gains when moving from disconnected planning to IBP. It also proposes a road map for the transformation of planning, including technological initiatives, business priorities and organizational processes, and demonstrates how to motivate different IBP stakeholders to work together, when and how to connect strategic (to be understood as long term SC&O), tactical and operational planning and how to leverage functional and data integration features of SAP IBP. Real-world business-process use cases help to show the practical implications of implementing SAP IBP. Furthermore the book explores new capabilities, talent acquisition and retention, career development leadership, IBP Center of Expertise. A discussion of how disruptive technology trends like big data, Internet of Things, machine learning and artificial intelligence can influence IBP now and in the near future rounds out the book. |
| erp master data management: SAP Billing and Revenue Innovation Management Chaitanaya Desai, Sheikna Kulam, Chun Wei Ooi, Maniprakash Balasubramanian, Clement Sanjivi, Andreas Tan, Rakesh Rajagopal, 2019 Whether you're upgrading an existing billing system or moving to a subscription- or consumption-based model, SAP BRIM is ready--and here's is your guide! From subscription order management and charging to invoicing and contract accounting, get step-by-step instructions for each piece of the billing puzzle. For setup, execution, or analytics, follow a continuous case study through each billing process. With this book, join the future of billing! a. End-to-End Billing Learn the what and the why of SAP BRIM, and then master the how! Charging, invoicing, contract accounts receivable and payable, and subscription order management--see how to streamline billing with the SAP BRIM solutions. b. Configuration and Functionality Set up and use SAP BRIM tools: Subscription Order Management, SAP Convergent Charging, SAP Convergent Invoicing, FI-CA, and more. Implement them individually or as part of an integrated landscape. c. SAP BRIM in Action Meet Martex Corp., a fictional telecommunications case study and your guide through the SAP BRIM suite. Follow its path to subscription-based billing and learn from billing industry best practices! 1) SAP Billing and Revenue Innovation Management 2) Subscription order management 3) SAP Convergent Charging 4) SAP Convergent Invoicing 5) Contracts accounting (FI-CA) 6) SAP Convergent Mediation 7) Reporting and analytics 8) Implementation 9) Project management |
| erp master data management: Electronic Government and Electronic Participation E. Tambouris, H.J. Scholl, M.F.W.H.A. Janssen, 2015-08-24 Electronic government and electronic participation continue to transform the public sector and society worldwide and are constantly being transformed themselves by emerging information and communication technologies. This book presents papers from the 14th International Federation for Information Processing’s EGOV conference (IFIP EGOV 2015), and its sister conference, the 7th Electronic Participation (ePart) conference, held in Thessaloniki, Greece, in August and September 2015 with the support and sponsorship of the University of Macedonia. Through the years, both of these conferences have established themselves as leading scientific events in their field, providing a forum for scholars to present and discuss their work. Included here are 31 accepted ongoing research papers, grouped under the following headings: eParticipation; policy modeling; open government and smart cities; general e-government; and e-government services; as well as 6 Ph.D. colloquium papers, 5 accepted posters and 3 workshops. With their combination of scientific credibility and rigor and with high relevance to practice, the papers presented here will be of interest to all those whose work involves electronic government and electronic participation. |
| erp master data management: Warehouse Management with SAP ERP Martin Murray, Sanil Kimmatkar, 2016 Ensure an efficient and orderly Warehouse Management implementation with this comprehensive guide to SAP WM in SAP ERP Learn to customize and use critical functionalities, like goods receipt and goods issue, as well as advanced technologies such as RFID, EDI, and mobile data entry. Covering everything from stock management to picking strategies, you'll master SAP WM. This new edition includes ITSmobile, connections with SAP ERP PP and QM, the warehouse activity monitor, and more. SAP WM Processes Grasp the essentials of warehouse management, including goods receipt, goods issue, replenishment, and putaway. Then master advanced topics such as hazardous materials management, cross-docking, and value-added services. SAP WM Configuration Understand the configuration details necessary to optimize your SAP WM implementation, from storage bins to yard management. Real World Scenarios Explore concrete business cases and examples to help you put expert tips into practice in your own warehouse. Highlights: -Stock management -Goods receipt and goods issue -Replenishment -Picking strategies -Putaway strategies -Inventory management -Yard management -Electronic Data Interchange (EDI) -Radio frequency identification (RFID) -ITSmobile |
| erp master data management: Enterprise Master Data Management Dreibelbis, 1900 This is the eBook version of the printed book. If the print book includes a CD-ROM, this content is not included within the eBook version. The Only Complete Technical Primer for Every MDM Planner and Implementer Companies moving toward flexible SOA architectures often face difficult information management and integration challenges. The lifeblood 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 and. |
| erp master data management: Data Governance John Ladley, 2019-11-08 Managing data continues to grow as a necessity for modern organizations. There are seemingly infinite opportunities for organic growth, reduction of costs, and creation of new products and services. It has become apparent that none of these opportunities can happen smoothly without data governance. The cost of exponential data growth and privacy / security concerns are becoming burdensome. Organizations will encounter unexpected consequences in new sources of risk. The solution to these challenges is also data governance; ensuring balance between risk and opportunity. Data Governance, Second Edition, is for any executive, manager or data professional who needs to understand or implement a data governance program. It is required to ensure consistent, accurate and reliable data across their organization. This book offers an overview of why data governance is needed, how to design, initiate, and execute a program and how to keep the program sustainable. This valuable resource provides comprehensive guidance to beginning professionals, managers or analysts looking to improve their processes, and advanced students in Data Management and related courses. With the provided framework and case studies all professionals in the data governance field will gain key insights into launching successful and money-saving data governance program. - Incorporates industry changes, lessons learned and new approaches - Explores various ways in which data analysts and managers can ensure consistent, accurate and reliable data across their organizations - Includes new case studies which detail real-world situations - Explores all of the capabilities an organization must adopt to become data driven - Provides guidance on various approaches to data governance, to determine whether an organization should be low profile, central controlled, agile, or traditional - Provides guidance on using technology and separating vendor hype from sincere delivery of necessary capabilities - Offers readers insights into how their organizations can improve the value of their data, through data quality, data strategy and data literacy - Provides up to 75% brand-new content compared to the first edition |
| erp master data management: Modern Enterprise Business Intelligence and Data Management Alan Simon, 2014-08-28 Nearly every large corporation and governmental agency is taking a fresh look at their current enterprise-scale business intelligence (BI) and data warehousing implementations at the dawn of the Big Data Era...and most see a critical need to revitalize their current capabilities. Whether they find the frustrating and business-impeding continuation of a long-standing silos of data problem, or an over-reliance on static production reports at the expense of predictive analytics and other true business intelligence capabilities, or a lack of progress in achieving the long-sought-after enterprise-wide single version of the truth – or all of the above – IT Directors, strategists, and architects find that they need to go back to the drawing board and produce a brand new BI/data warehousing roadmap to help move their enterprises from their current state to one where the promises of emerging technologies and a generation's worth of best practices can finally deliver high-impact, architecturally evolvable enterprise-scale business intelligence and data warehousing. Author Alan Simon, whose BI and data warehousing experience dates back to the late 1970s and who has personally delivered or led more than thirty enterprise-wide BI/data warehousing roadmap engagements since the mid-1990s, details a comprehensive step-by-step approach to building a best practices-driven, multi-year roadmap in the quest for architecturally evolvable BI and data warehousing at the enterprise scale. Simon addresses the triad of technology, work processes, and organizational/human factors considerations in a manner that blends the visionary and the pragmatic. - Takes a fresh look at true enterprise-scale BI/DW in the Dawn of the Big Data Era - Details a checklist-based approach to surveying one's current state and identifying which components are enterprise-ready and which ones are impeding the key objectives of enterprise-scale BI/DW - Provides an approach for how to analyze and test-bed emerging technologies and architectures and then figure out how to include the relevant ones in the roadmaps that will be developed - Presents a tried-and-true methodology for building a phased, incremental, and iterative enterprise BI/DW roadmap that is closely aligned with an organization's business imperatives, organizational culture, and other considerations |
| erp master data management: ERP Systems for Manufacturing Supply Chains Odd Jøran Sagegg, Erlend Alfnes, 2020-02-24 ERP Systems for Manufacturing Supply Chains: Applications, Configuration, and Performance provides insight into the core architecture, modules, and process support of ERP systems used in a manufacturing supply chain. This book explains the building blocks of an ERP system and how they can be used to increase performance of manufacturing supply chains. Starting with an overview of basic concepts of supply chain and ERP systems, the book delves into the core ERP modules that support manufacturing facilities and organizations. It examines each module’s structure and functionality as well as the process support the module provides. Cases illustrate how the modules can be applied in manufacturing environments. Also covered is how the ERP modules can be configured to support manufacturing supply chains. Setting up an ERP system to support the supply chain within single manufacturing facility provides insight into how an ERP system is used in the smallest of manufacturing enterprises, as well as lays the foundation for ERP systems in manufacturing organizations. The book then supplies strategies for larger manufacturing enterprises and discusses how ERP systems can be used to support a complete manufacturing supply chain across different facilities and companies. The ERP systems on the market today tend to use common terminology and naming for describing specific functions and data units in the software. However, there are differences among packages. The book discusses various data and functionalities found in different ERP-software packages and uses generic and descriptive terms as often as possible to make these valid for as many ERP systems as possible. Filled with insight into ERP system’s core modules and functions, this book shows how ERP systems can be applied to support a supply chain in the smallest of manufacturing organizations that only consist of a single manufacturing facility, as well as large enterprises where the manufacturing supply chain crosses multiple facilities and companies. |
| erp master data management: Directing the ERP Implementation Michael W. Pelphrey, 2015-04-02 Although many books outline approaches for successful ERP implementations, the data shows that most ERP efforts yield minimal return on investment (ROI), with most projects failing. Directing the ERP Implementation: A Best Practice Guide to Avoiding Program Failure Traps While Tuning System Performance supplies best practices along with a proven ro |
| erp master data management: Manufacturing Execution System - MES Jürgen Kletti, 2007-05-01 Decisive potential in business is a question of process capability, rather than production capability. Process capability in business requires real-time systems for optimization. Business-IT needs to be developed from telecommunications and ERP to real-time services, which are not offered by the prevailing ERP systems. This book shows how modern information technology Manufacturing Execution Systems (MES) becomes the prerequisite for process capability of the company on the basis of many practical examples. It describes the requirements for optimized MES. It gives an overview of the efficiency potentials and different applications of MES. |
| erp master data management: Compendium on Enterprise Resource Planning Siar Sarferaz, 2022-04-01 This book explains the functional scope, the data model, the solution architecture, the underlying engineering concepts, and the programming model of SAP S/4HANA as the most well-known enterprise resource planning (ERP) system. The approach is to start with general concepts and then to proceed step-by-step to concrete implementations in SAP S/4HANA. In the first part the reader learns about the market view of ERP solutions and vendors. The second part deals with the business processes for sales, marketing, finance, supply chain, manufacturing, services, procurement, and human resources which are covered with SAP S/4HANA. In the third part the underlying concepts of SAP S/4HANA are described, for example in-memory storage, analytics and search, artificial intelligence, process and data integration, security and compliance, lifecycle management, performance and scalability, configuration and implementation. The book is concluded with a final chapter explaining how to deploy an appliance to explore SAP S/4HANA. The target audience for the book are managers and business analysts who want to understand the market situation and future ERP trends, end users and process experts who need to comprehend the business processes and the according solution capabilities provided with SAP S/4HANA, architects and developers who have to learn the technical concepts and frameworks for enhancing SAP S/4HANA functionality, and consultants and partners who require to adopt and configure SAP S/4HANA. |
| erp master data management: SAP Product Lifecycle Management Hanneke Raap, 2013 Do you struggle with managing the all-encompassing product lifecycle, and need a comprehensive guide to the SAP Product Lifecycle Management solution? Look no further. This long-anticipated, up-to-date resource is your answer. Within these pages, youll find the comprehensive, functional overview of SAP PLM, from what it is to how it can benefit your business, with a plethora of business scenarios and processes included throughout. Youll learn how each PLM business process is supported by which part of the application, and how to implement those solutions. Whether youre a consultant, project manager, or part of the implementation teamyoull find what you need to prepare yourself to use the system effectively. |
| erp master data management: Army Logistician , 2006 |
| erp master data management: Advances in Conceptual Modeling - Theory and Practice John F. Roddick, 2006-10-24 This book constitutes the refereed joint proceedings of seven international workshops held in conjunction with the 25th International Conference on Conceptual Modeling, ER 2006, in Tucson, AZ, USA in November 2006. The 39 revised full papers presented together with the outlines of three tutorials were carefully reviewed and selected from 95 submissions. |
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