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| customer data management solutions: 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 |
| customer data management solutions: 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 |
| customer data management solutions: Customer Data Platforms Martin Kihn, Christopher B. O'Hara, 2020-11-06 Master the hottest technology around to drive marketing success Marketers are faced with a stark and challenging dilemma: customers demand deep personalization, but they are increasingly leery of offering the type of personal data required to make it happen. As a solution to this problem, Customer Data Platforms have come to the fore, offering companies a way to capture, unify, activate, and analyze customer data. CDPs are the hottest marketing technology around today, but are they worthy of the hype? Customer Data Platforms takes a deep dive into everything CDP so you can learn how to steer your firm toward the future of personalization. Over the years, many of us have built byzantine “stacks” of various marketing and advertising technology in an attempt to deliver the fabled “right person, right message, right time” experience. This can lead to siloed systems, disconnected processes, and legacy technical debt. CDPs offer a way to simplify the stack and deliver a balanced and engaging customer experience. Customer Data Platforms breaks down the fundamentals, including how to: Understand the problems of managing customer data Understand what CDPs are and what they do (and don't do) Organize and harmonize customer data for use in marketing Build a safe, compliant first-party data asset that your brand can use as fuel Create a data-driven culture that puts customers at the center of everything you do Understand how to use AI and machine learning to drive the future of personalization Orchestrate modern customer journeys that react to customers in real-time Power analytics with customer data to get closer to true attribution In this book, you’ll discover how to build 1:1 engagement that scales at the speed of today’s customers. |
| customer data management solutions: 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 |
| customer data management solutions: 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 |
| customer data management solutions: 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. |
| customer data management solutions: 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. |
| customer data management solutions: Building the Customer-Centric Enterprise Claudia Imhoff, Lisa Loftis, Jonathan G. Geiger, 2001-02-19 Strategies for leveraging information technologies to improve customer relationships With E-business comes the opportunity for companies to really get to know their customers--who they are and their buying patterns. Business managers need an integrated strategy that supports customers from the moment they enter the front door--or Web site--right through to fulfillment, support, and promotion of new products and services. Along the way, IT managers need an integrated set of technologies--from Web sites to databases and data mining tools--to make all of this work. This book shows both IT and business managers how to match business strategies to the technologies needed to make them work. Claudia Imhoff helped pioneer this set of technologies, called the Corporate Information Factory (CIF). She and her coauthors take readers step-by-step through the process of using the CIF for creating a customer-focused enterprise in which the end results are increased market share and improved customer satisfaction and retention. They show how the CIF can be used to ensure accuracy, identify customer needs, tailor promotions, and more. |
| customer data management solutions: Business Intelligence Guidebook Rick Sherman, 2014-11-04 Between the high-level concepts of business intelligence and the nitty-gritty instructions for using vendors' tools lies the essential, yet poorly-understood layer of architecture, design and process. Without this knowledge, Big Data is belittled – projects flounder, are late and go over budget. Business Intelligence Guidebook: From Data Integration to Analytics shines a bright light on an often neglected topic, arming you with the knowledge you need to design rock-solid business intelligence and data integration processes. Practicing consultant and adjunct BI professor Rick Sherman takes the guesswork out of creating systems that are cost-effective, reusable and essential for transforming raw data into valuable information for business decision-makers. After reading this book, you will be able to design the overall architecture for functioning business intelligence systems with the supporting data warehousing and data-integration applications. You will have the information you need to get a project launched, developed, managed and delivered on time and on budget – turning the deluge of data into actionable information that fuels business knowledge. Finally, you'll give your career a boost by demonstrating an essential knowledge that puts corporate BI projects on a fast-track to success. - Provides practical guidelines for building successful BI, DW and data integration solutions. - Explains underlying BI, DW and data integration design, architecture and processes in clear, accessible language. - Includes the complete project development lifecycle that can be applied at large enterprises as well as at small to medium-sized businesses - Describes best practices and pragmatic approaches so readers can put them into action. - Companion website includes templates and examples, further discussion of key topics, instructor materials, and references to trusted industry sources. |
| customer data management solutions: Oracle Case Management Solutions Léon Smiers, Manas Deb, Joop Koster, Prasen Palvankar, 2015-10-28 Organizations increasingly need to deal with unstructured processes that traditional business process management (BPM) suites are not designed to deal with. High-risk, yet high-value, loan origination or credit approvals, police investigations, and healthcare patient treatment are just a few examples of areas where a level of uncertainty makes outc |
| customer data management solutions: 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. |
| customer data management solutions: 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. |
| customer data management solutions: Data Driven Thomas C. Redman, 2008-09-22 Your company's data has the potential to add enormous value to every facet of the organization -- from marketing and new product development to strategy to financial management. Yet if your company is like most, it's not using its data to create strategic advantage. Data sits around unused -- or incorrect data fouls up operations and decision making. In Data Driven, Thomas Redman, the Data Doc, shows how to leverage and deploy data to sharpen your company's competitive edge and enhance its profitability. The author reveals: · The special properties that make data such a powerful asset · The hidden costs of flawed, outdated, or otherwise poor-quality data · How to improve data quality for competitive advantage · Strategies for exploiting your data to make better business decisions · The many ways to bring data to market · Ideas for dealing with political struggles over data and concerns about privacy rights Your company's data is a key business asset, and you need to manage it aggressively and professionally. Whether you're a top executive, an aspiring leader, or a product-line manager, this eye-opening book provides the tools and thinking you need to do that. |
| customer data management solutions: Customer Data Platforms Martin Kihn, Christopher B. O'Hara, 2020-12-15 Master the hottest technology around to drive marketing success Marketers are faced with a stark and challenging dilemma: customers demand deep personalization, but they are increasingly leery of offering the type of personal data required to make it happen. As a solution to this problem, Customer Data Platforms have come to the fore, offering companies a way to capture, unify, activate, and analyze customer data. CDPs are the hottest marketing technology around today, but are they worthy of the hype? Customer Data Platforms takes a deep dive into everything CDP so you can learn how to steer your firm toward the future of personalization. Over the years, many of us have built byzantine “stacks” of various marketing and advertising technology in an attempt to deliver the fabled “right person, right message, right time” experience. This can lead to siloed systems, disconnected processes, and legacy technical debt. CDPs offer a way to simplify the stack and deliver a balanced and engaging customer experience. Customer Data Platforms breaks down the fundamentals, including how to: Understand the problems of managing customer data Understand what CDPs are and what they do (and don't do) Organize and harmonize customer data for use in marketing Build a safe, compliant first-party data asset that your brand can use as fuel Create a data-driven culture that puts customers at the center of everything you do Understand how to use AI and machine learning to drive the future of personalization Orchestrate modern customer journeys that react to customers in real-time Power analytics with customer data to get closer to true attribution In this book, you’ll discover how to build 1:1 engagement that scales at the speed of today’s customers. |
| customer data management solutions: 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 |
| customer data management solutions: Proceedings of Data Analytics and Management Deepak Gupta, Zdzislaw Polkowski, Ashish Khanna, Siddhartha Bhattacharyya, Oscar Castillo, 2022-01-04 This book includes original unpublished contributions presented at the International Conference on Data Analytics and Management (ICDAM 2021), held at Jan Wyzykowski University, Poland, during June 2021. The book covers the topics in data analytics, data management, big data, computational intelligence, and communication networks. The book presents innovative work by leading academics, researchers, and experts from industry which is useful for young researchers and students. |
| customer data management solutions: 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. |
| customer data management solutions: Customer Knowledge Management: People, Processes, and Technology Al-Shammari, Minwir, 2009-03-31 This book introduces an integrated approach to analyzing and building customer knowledge management (CKM) synergy from distinctive core advantages found in key organizational elements--Provided by publisher. |
| customer data management solutions: Data Management Solutions Using SAS Hash Table Operations Paul Dorfman, Don Henderson, 2018-07-09 Hash tables can do a lot more than you might think! Data Management Solutions Using SAS Hash Table Operations: A Business Intelligence Case Study concentrates on solving your challenging data management and analysis problems via the power of the SAS hash object, whose environment and tools make it possible to create complete dynamic solutions. To this end, this book provides an in-depth overview of the hash table as an in-memory database with the CRUD (Create, Retrieve, Update, Delete) cycle rendered by the hash object tools. By using this concept and focusing on real-world problems exemplified by sports data sets and statistics, this book seeks to help you take advantage of the hash object productively, in particular, but not limited to, the following tasks: select proper hash tools to perform hash table operations use proper hash table operations to support specific data management tasks use the dynamic, run-time nature of hash object programming understand the algorithmic principles behind hash table data look-up, retrieval, and aggregation learn how to perform data aggregation, for which the hash object is exceptionally well suited manage the hash table memory footprint, especially when processing big data use hash object techniques for other data processing tasks, such as filtering, combining, splitting, sorting, and unduplicating. Using this book, you will be able to answer your toughest questions quickly and in the most efficient way possible! |
| customer data management solutions: Open Source Customer Relationship Management Solutions Henrik Vogt, 2008 The book reveals the overall importance of a customer relationship management system especially for small and medium-sized enterprises. In addition to the topic of CRM, the increasing importance and possibilities of open source software is revealed.The main research question consists of the idea if open source customer relationship management systems are able to fulfill the requirements of a CRM software.In order to be able to answer this question, the following analysis made use of the literature available on the topics CRM, special requirements of small and medium-sized enterprises, and the topic of open source software.By revealing what a CRM have to fulfill in order to be classified as customer relationship management system according to the findings in the literature, various requirements are identified.In the next step, the three most popular open source CRM software systems Sugar CRM, vTiger, and OpenCRX are scrutinized under the criteria if they are able to fulfill the requirements defined in the previous steps.The conclusion discusses the previous findings and outlines the chances and limits of open source customer relationship management solutions for small and medium-sized enterprises.In addition to this, the requirements of a successful implementation of a CRM system are revealed and the concept of seeing CRM as a corporate strategy is concretized.The aim of this book is to outline the holistic approach of CRM and to examine the research question if open source CRM solutions are able to fulfill the requirements previously defined according to the underlying literature. |
| customer data management solutions: CRM in Financial Services Bryan Foss, Merlin Stone, 2002 Packed with international case studies and examples, the book begins with a detailed analysis of the state of CRM and e-business in the financial services globally, and then goes on to provide comprehensive and practical guidance on: making the most of your customer base; systems and data management; risk and compliance; channels and value chain issues; implementation; strategic implications. |
| customer data management solutions: Microsoft Access Small Business Solutions Teresa Hennig, Truitt L. Bradly, Larry Linson, Leigh Purvis, Brent Spaulding, 2010-02-18 Database models developed by a team of leading Microsoft Access MVPs that provide ready-to-use solutions for sales, marketing, customer management and other key business activities for most small businesses. As the most popular relational database in the world, Microsoft Access is widely used by small business owners. This book responds to the growing need for resources that help business managers and end users design and build effective Access database solutions for specific business functions. Coverage includes: Elements of a Microsoft Access Database Relational Data Model Dealing with Customers and Customer Data Customer Relationship Management Database Solutions Marketing Database Solutions Sales Database Solutions Producing and Tracking the Goods & Services Production and Manufacturing Database Solutions Inventory Management Database Solutions Services Database Solutions Tracking and Analyzing Financial Data 1 Accounting Systems: Requirements and Design Database Solutions Accounting: Budgeting, Analysis, and Reporting Database Solutions Managing Memberships Implementing the Models SQL Server and Other External Data Sources With this valuable guide and CD-ROM, you'll be on your way to implementing database solutions in no time |
| customer data management solutions: Plunkett's Outsourcing & Offshoring Industry Almanac Jack W. Plunkett, 2008-06 Market research guide to the outsourcing and offshoring industry a tool for strategic planning, competitive intelligence, employment searches or financial research. Contains trends, statistical tables, and an industry glossary. Over 300 one page profiles of Outsourcing Offshoring Industry Firms - includes addresses, phone numbers, executive names. |
| customer data management solutions: IBM Information Governance Solutions Chuck Ballard, John Baldwin, Alex Baryudin, Gary Brunell, Christopher Giardina, Marc Haber, Erik A O'neill, Sandeep Shah, IBM Redbooks, 2014-04-04 Managing information within the enterprise has always been a vital and important task to support the day-to-day business operations and to enable analysis of that data for decision making to better manage and grow the business for improved profitability. To do all that, clearly the data must be accurate and organized so it is accessible and understandable to all who need it. That task has grown in importance as the volume of enterprise data has been growing significantly (analyst estimates of 40 - 50% growth per year are not uncommon) over the years. However, most of that data has been what we call structured data, which is the type that can fit neatly into rows and columns and be more easily analyzed. Now we are in the era of big data. This significantly increases the volume of data available, but it is in a form called unstructured data. That is, data from sources that are not as easily organized, such as data from emails, spreadsheets, sensors, video, audio, and social media sites. There is valuable information in all that data but it calls for new processes to enable it to be analyzed. All this has brought with it a renewed and critical need to manage and organize that data with clarity of meaning, understandability, and interoperability. That is, you must be able to integrate this data when it is from within an enterprise but also importantly when it is from many different external sources. What is described here has been and is being done to varying extents. It is called information governance. Governing this information however has proven to be challenging. But without governance, much of the data can be less useful and perhaps even used incorrectly, significantly impacting enterprise decision making. So we must also respect the needs for information security, consistency, and validity or else suffer the potential economic and legal consequences. Implementing sound governance practices needs to be an integral part of the information control in our organizations. This IBM® Redbooks® publication focuses on the building blocks of a solid governance program. It examines some familiar governance initiative scenarios, identifying how they underpin key governance initiatives, such as Master Data Management, Quality Management, Security and Privacy, and Information Lifecycle Management. IBM Information Management and Governance solutions provide a comprehensive suite to help organizations better understand and build their governance solutions. The book also identifies new and innovative approaches that are developed by IBM practice leaders that can help as you implement the foundation capabilities in your organizations. |
| customer data management solutions: The Semantic Web - ISWC 2009 Abraham Bernstein, David R. Karger, Tom Heath, Lee Feigenbaum, Diana Maynard, Enrico Motta, Krishnaprasad Thirunarayan, 2009-11-06 As the Web continues to grow, increasing amounts of data are being made available for human and machine consumption. This emerging Semantic Web is rapidly entering the mainstream and, as a result, a variety of new solutions for searching, aggregating and the intelligent delivery of information are being produced,bothinresearchandcommercialsettings.Severalnewchallengesarise from this context, both from a technical and human–computer interaction p- spective – e.g., as issues to do with the scalability andusability of Semantic Web solutions become particularly important. The International Semantic Web Conference (ISWC) is the major inter- tional forum where the latest research results and technical innovations on all aspects of the Semantic Web are presented. ISWC brings together researchers, practitioners, and users from the areas of arti?cial intelligence, databases, social networks,distributedcomputing,Webengineering,informationsystems,natural language processing, soft computing, and human–computer interaction to d- cuss the major challenges and proposed solutions, success stories and failures, as well the visions that can advance the ?eld. |
| customer data management solutions: Plunkett's Outsourcing & Offshoring Industry Almanac: Outsourcing and Offshoring Industry Market Research, Statistics, Trends & Leading Companies Jack W. Plunkett, 2007-07 Contains trends, statistical tables, and an industry glossary. This almanac presents over 300 profiles of outsourcing and offshoring industry firms. It also includes addresses, phone numbers, and executives. |
| customer data management solutions: The Modern Data Warehouse in Azure Matt How, 2020-06-15 Build a modern data warehouse on Microsoft's Azure Platform that is flexible, adaptable, and fast—fast to snap together, reconfigure, and fast at delivering results to drive good decision making in your business. Gone are the days when data warehousing projects were lumbering dinosaur-style projects that took forever, drained budgets, and produced business intelligence (BI) just in time to tell you what to do 10 years ago. This book will show you how to assemble a data warehouse solution like a jigsaw puzzle by connecting specific Azure technologies that address your own needs and bring value to your business. You will see how to implement a range of architectural patterns using batches, events, and streams for both data lake technology and SQL databases. You will discover how to manage metadata and automation to accelerate the development of your warehouse while establishing resilience at every level. And you will know how to feed downstream analytic solutions such as Power BI and Azure Analysis Services to empower data-driven decision making that drives your business forward toward a pattern of success. This book teaches you how to employ the Azure platform in a strategy to dramatically improve implementation speed and flexibility of data warehousing systems. You will know how to make correct decisions in design, architecture, and infrastructure such as choosing which type of SQL engine (from at least three options) best meets the needs of your organization. You also will learn about ETL/ELT structure and the vast number of accelerators and patterns that can be used to aid implementation and ensure resilience. Data warehouse developers and architects will find this book a tremendous resource for moving their skills into the future through cloud-based implementations. What You Will LearnChoose the appropriate Azure SQL engine for implementing a given data warehouse Develop smart, reusable ETL/ELT processes that are resilient and easily maintained Automate mundane development tasks through tools such as PowerShell Ensure consistency of data by creating and enforcing data contracts Explore streaming and event-driven architectures for data ingestionCreate advanced staging layers using Azure Data Lake Gen 2 to feed your data warehouse Who This Book Is For Data warehouse or ETL/ELT developers who wish to implement a data warehouse project in the Azure cloud, and developers currently working in on-premise environments who want to move to the cloud, and for developers with Azure experience looking to tighten up their implementation and consolidate their knowledge |
| customer data management solutions: Sales Engagement Manny Medina, Max Altschuler, Mark Kosoglow, 2019-03-12 Engage in sales—the modern way Sales Engagement is how you engage and interact with your potential buyer to create connection, grab attention, and generate enough interest to create a buying opportunity. Sales Engagement details the modern way to build the top of the funnel and generate qualified leads for B2B companies. This book explores why a Sales Engagement strategy is so important, and walks you through the modern sales process to ensure you’re effectively connecting with customers every step of the way. • Find common factors holding your sales back—and reverse them through channel optimization • Humanize sales with personas and relevant information at every turn • Understand why A/B testing is so incredibly critical to success, and how to do it right • Take your sales process to the next level with a rock solid, modern Sales Engagement strategy This book is essential reading for anyone interested in up-leveling their game and doing more than they ever thought possible. |
| customer data management solutions: Data Science and Big Data Computing Zaigham Mahmood, 2016-07-05 This illuminating text/reference surveys the state of the art in data science, and provides practical guidance on big data analytics. Expert perspectives are provided by authoritative researchers and practitioners from around the world, discussing research developments and emerging trends, presenting case studies on helpful frameworks and innovative methodologies, and suggesting best practices for efficient and effective data analytics. Features: reviews a framework for fast data applications, a technique for complex event processing, and agglomerative approaches for the partitioning of networks; introduces a unified approach to data modeling and management, and a distributed computing perspective on interfacing physical and cyber worlds; presents techniques for machine learning for big data, and identifying duplicate records in data repositories; examines enabling technologies and tools for data mining; proposes frameworks for data extraction, and adaptive decision making and social media analysis. |
| customer data management solutions: Coherency Management Gary Doucet, Pallab Saha, Scott Bernard, 2009 The book introduces the idea of Coherency Management, and asserts that this is the primary outcome goal of an enterprise's architecture. With submissions from over 30 authors and co-authors, the book reinforces the idea that EA is being practiced in an ever-increasing variety of circumstances - from the tactical to the strategic, from the technical to the political, and with governance that ranges from sell to tell. The characteristics, usages, value statements, frameworks, rules, tools and countless other attributes of EA seem to be anything but orderly, definable, classifiable, and understandable as might be hoped given heritage of EA and the famous framework and seminal article on the subject by John Zachman over two decades ago. Notably, EA is viewed as an Enterprise Design and Management approach, adopted to build better enterprises, rather than a IT Design and Management approach limited to build better systems. |
| customer data management solutions: Process Automation Strategy in Services, Manufacturing and Construction Bharati Mohapatra, Sanjana Mohapatra, Sanjay Mohapatra, 2023-02-20 Appealing to business researchers, academics and practitioners, Process Automation Strategy in Services, Manufacturing and Construction brings to life the current trends in process automation and considers what the future holds. |
| customer data management solutions: CIO , 2006-08-01 |
| customer data management solutions: Information-Driven Business Robert Hillard, 2010-08-23 Information doesn't just provide a window on the business, increasingly it is the business. The global economy is moving from products to services which are described almost entirely electronically. Even those businesses that are traditionally associated with making things are less concerned with managing the manufacturing process (which is largely outsourced) than they are with maintaining their intellectual property. Information-Driven Business helps you to understand this change and find the value in your data. Hillard explains techniques that organizations can use and how businesses can apply them immediately. For example, simple changes to the way data is described will let staff support their customers much more quickly; and two simple measures let executives know whether they will be able to use the content of a database before it is even built. This book provides the foundation on which analytical and data rich organizations can be created. Innovative and revealing, this book provides a robust description of Information Management theory and how you can pragmatically apply it to real business problems, with almost instant benefits. Information-Driven Business comprehensively tackles the challenge of managing information, starting with why information has become important and how it is encoded, through to how to measure its use. |
| customer data management solutions: Data Governance John Ladley, 2012-11-07 This book is for any manager or team leader that has the green light to implement a data governance program. The problem of managing data continues to grow with issues surrounding cost of storage, exponential growth, as well as administrative, management and security concerns – the solution to being able to scale all of these issues up is data governance which provides better services to users and saves money. 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. With the provided framework and case studies you will be enabled and educated in launching your very own successful and money saving data governance program. - Provides a complete overview of the data governance lifecycle, that can help you discern technology and staff needs - Specifically aimed at managers who need to implement a data governance program at their company - Includes case studies to detail 'do's' and 'don'ts' in real-world situations |
| customer data management solutions: The CIO's Guide to Oracle Products and Solutions Jessica Keyes, 2014-09-02 From operating systems to the cloud, Oracle's products and services are everywhere, and it has the market share to prove it. Given the share diversity of the Oracle product line, and the level of complexity of integration, management can be quite a daunting task.The CIO's Guide to Oracle Products and Solutions is the go-to guide for all things Orac |
| customer data management solutions: Applications of Data Management and Analysis Mohammad Moshirpour, Behrouz H. Far, Reda Alhajj, 2018-10-04 This book addresses and examines the impacts of applications and services for data management and analysis, such as infrastructure, platforms, software, and business processes, on both academia and industry. The chapters cover effective approaches in dealing with the inherent complexity and increasing demands of big data management from an applications perspective. Various case studies included have been reported by data analysis experts who work closely with their clients in such fields as education, banking, and telecommunications. Understanding how data management has been adapted to these applications will help students, instructors and professionals in the field. Application areas also include the fields of social network analysis, bioinformatics, and the oil and gas industries. |
| customer data management solutions: Enterprise Data at Huawei Yun Ma, Hao Du, 2021-11-22 This book systematically introduces the data governance and digital transformation at Huawei, from the perspectives of technology, process, management, and so on. Huawei is a large global enterprise engaging in multiple types of business in over 170 countries and regions. Its differentiated operation is supported by an enterprise data foundation and corresponding data governance methods. With valuable experience, methodology, standards, solutions, and case studies on data governance and digital transformation, enterprise data at Huawei is ideal for readers to learn and apply, as well as to get an idea of the digital transformation journey at Huawei. This book is organized into four parts and ten chapters. Based on the understanding of “the cognitive world of machines,” the book proposes the prospects for the future of data governance, as well as the imaginations about AI-based governance, data sovereignty, and building a data ecosystem. |
| customer data management solutions: Advanced Methodologies and Technologies in Business Operations and Management Khosrow-Pour, D.B.A., Mehdi, 2018-09-14 Businesses consistently work on new projects, products, and workflows to remain competitive and successful in the modern business environment. To remain zealous, businesses must employ the most effective methods and tools in human resources, project management, and overall business plan execution as competitors work to succeed as well. Advanced Methodologies and Technologies in Business Operations and Management provides emerging research on business tools such as employee engagement, payout policies, and financial investing to promote operational success. While highlighting the challenges facing modern organizations, readers will learn how corporate social responsibility and utilizing artificial intelligence improve a company’s culture and management. This book is an ideal resource for executives and managers, researchers, accountants, and financial investors seeking current research on business operations and management. |
| customer data management solutions: Official Gazette of the United States Patent and Trademark Office , 2004 |
| customer data management solutions: Predictive Marketing Omer Artun, Dominique Levin, 2015-08-06 Make personalized marketing a reality with this practical guide to predictive analytics Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tips and actionable strategies for implementing more personalized marketing immediately. The marketing paradigm is changing, and this book provides a blueprint for navigating the transition from creative- to data-driven marketing, from one-size-fits-all to one-on-one, and from marketing campaigns to real-time customer experiences. You'll learn how to use machine-learning technologies to improve customer acquisition and customer growth, and how to identify and re-engage at-risk or lapsed customers by implementing an easy, automated approach to predictive analytics. Much more than just theory and testament to the power of personalized marketing, this book focuses on action, helping you understand and actually begin using this revolutionary approach to the customer experience. Predictive analytics can finally make personalized marketing a reality. For the first time, predictive marketing is accessible to all marketers, not just those at large corporations — in fact, many smaller organizations are leapfrogging their larger counterparts with innovative programs. This book shows you how to bring predictive analytics to your organization, with actionable guidance that get you started today. Implement predictive marketing at any size organization Deliver a more personalized marketing experience Automate predictive analytics with machine learning technology Base marketing decisions on concrete data rather than unproven ideas Marketers have long been talking about delivering personalized experiences across channels. All marketers want to deliver happiness, but most still employ a one-size-fits-all approach. Predictive Marketing provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience. |
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Customer Data Architecture - Accenture
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the fujitsu master data management solution helps organizations identify and maintain A SINGLE, CONSISTENT VIEW OF BUSINESS CRITICAL DATA THAT IS OFTEN LOCKED, …
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the strategy, innovation and marketing literatures in an integrative way. Our exposition of the mechanisms emphasizes that our two mechanisms, separately or jointly, generate potentially …
Customer Data Management CDM Strategies - Oracle
Customer data management (CDM) is a set of processes and technologies that enable the ethical collection, secure storage, and proper maintenance of customer information. CDM systems …
Customer-Management-Solutions-for-Fintech - datamatics.com
customer timeline, real-time reporting and drill-down dashboards. With better customer context and a ‘single view across all transactions & mediums’, our agents were able to respond (and …
CUSTOMER RELATIONSHIP MANAGEMENT (CRM) SYSTEMS: …
CRM systems centralize and streamline customer data from various channels, enabling businesses to gain a comprehensive view of each customer. This consolidation facilitates …
The Forrester New Wave™: B2B Customer Data Platforms, Q2 20
enterprise data management, analytics, ERP, nance, and customer service)? Which applications or functional areas do its customers use? Does the vendor have a compelling and credible …
Oracle Master Data Management: Executive Overview
Oracle’s technology components are ideal for building master data management systems, and Oracle’s pre-built MDM solutions for key master data objects such as Product, Customer, Site, …
MASTER DATA MANAGEMENT (MDM) FOR INSURANCE
Leading-edge Master Data Management (MDM) solutions can provide a comprehensive data management strategy for insurers to further customer engagement, and gain deeper insights …
Oracle Fusion MDM
Customer Data Management (CDM) is the term for using MDM technologies to centralize customer data. CDM helps enterprises harmonize data across customer-centric applications …
A DATA DRIVEN APPROACH TO IMPROVE CUSTOMER …
While capturing customer data is only a part of the solution, organizations need to improve their maturity on Data Led Customer Engagement (DLCE) to build strategic data use cases that …
Customer 360 Software as a Service (SaaS) - Informatica
Informatica® Customer 360 SaaS is a modern, intelligent, all-in-one customer data management solution designed for building an eficient discovery, operations, insights, and analytics …
The Essential Guide to Customer Data Platform Success
The most commonly used data sources for customer data are customer relationship management (CRM) systems, email campaign solutions, website analytics tools, social media platforms, …
A Guide to Selecting the Right Customer Data Platform (CDP)
Understanding Customer Data Platforms: • Identity – How is customer data linked, persisted and refreshed, can it do deterministic cross-device matching and probabilistic matching. • Data …
Multi-Domain MDM: Mastering Modern Data Management …
Multi-Domain MDM with a Product Master Domain helps companies: Aggregate and consolidate product information, delivering accurate and consistent information from a single source of data.
Customer Data Architecture - Accenture
Single view of the customer Reduce media wastage Free up 10-20% of digital media budget 5-10% growth in revenue from media management Our results Decentralized data Fragmented …
IBM Customer Care Solutions
• Simplify organizational customer data management. Companies can maintain an authoritative record of corporate customer data in a single location. • Create targeted, effective corporate …
Oracle Solutions for Customer Experience
Customer data platform • Unify fragmented customer data across front- and back-office systems and third-party sources to build a 360-degree customer view at the account and contact level • …
NOVEMBER 2020 The ABCs of Customer Data in Marketing
This primer aims to help to spell out what each type of customer data . management system is designed to do—and even more important, what it is not designed to do—so you can make …
CASE STUDY MASTER DATA MANAGEMENT - Fujitsu Global
the fujitsu master data management solution helps organizations identify and maintain A SINGLE, CONSISTENT VIEW OF BUSINESS CRITICAL DATA THAT IS OFTEN LOCKED, …
The future of managing customer data: Beyond GDPR …
Together, we have a compelling technology solution in single customer views, legal and compliance monitoring, analytics, machine learning, modelling platforms, cloud data …
Deliver Personalized Experiences with a Customer Data …
CUSTOMER DATA PLATFORM (CDP): A collection of software solutions that brings together all of an institution’s customer data to create unified customer profiles. Sources of the customer …
Generating and Leveraging Customer Data Assets:
the strategy, innovation and marketing literatures in an integrative way. Our exposition of the mechanisms emphasizes that our two mechanisms, separately or jointly, generate potentially …
Customer Data Management CDM Strategies - Oracle
Customer data management (CDM) is a set of processes and technologies that enable the ethical collection, secure storage, and proper maintenance of customer information. CDM systems …
Customer-Management-Solutions-for-Fintech
customer timeline, real-time reporting and drill-down dashboards. With better customer context and a ‘single view across all transactions & mediums’, our agents were able to respond (and …
CUSTOMER RELATIONSHIP MANAGEMENT (CRM) SYSTEMS: …
CRM systems centralize and streamline customer data from various channels, enabling businesses to gain a comprehensive view of each customer. This consolidation facilitates …
The Forrester New Wave™: B2B Customer Data Platforms, Q2 …
enterprise data management, analytics, ERP, nance, and customer service)? Which applications or functional areas do its customers use? Does the vendor have a compelling and credible …
Oracle Master Data Management: Executive Overview
Oracle’s technology components are ideal for building master data management systems, and Oracle’s pre-built MDM solutions for key master data objects such as Product, Customer, Site, …
MASTER DATA MANAGEMENT (MDM) FOR INSURANCE
Leading-edge Master Data Management (MDM) solutions can provide a comprehensive data management strategy for insurers to further customer engagement, and gain deeper insights …
