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| data management operating model: Non-Invasive Data Governance Robert S. Seiner, 2014-09-01 Data-governance programs focus on authority and accountability for the management of data as a valued organizational asset. Data Governance should not be about command-and-control, yet at times could become invasive or threatening to the work, people and culture of an organization. Non-Invasive Data Governance™ focuses on formalizing existing accountability for the management of data and improving formal communications, protection, and quality efforts through effective stewarding of data resources. Non-Invasive Data Governance will provide you with a complete set of tools to help you deliver a successful data governance program. Learn how: • Steward responsibilities can be identified and recognized, formalized, and engaged according to their existing responsibility rather than being assigned or handed to people as more work. • Governance of information can be applied to existing policies, standard operating procedures, practices, and methodologies, rather than being introduced or emphasized as new processes or methods. • Governance of information can support all data integration, risk management, business intelligence and master data management activities rather than imposing inconsistent rigor to these initiatives. • A practical and non-threatening approach can be applied to governing information and promoting stewardship of data as a cross-organization asset. • Best practices and key concepts of this non-threatening approach can be communicated effectively to leverage strengths and address opportunities to improve. |
| data management operating model: Performance Dashboards Wayne W. Eckerson, 2005-10-27 Tips, techniques, and trends on how to use dashboard technology to optimize business performance Business performance management is a hot new management discipline that delivers tremendous value when supported by information technology. Through case studies and industry research, this book shows how leading companies are using performance dashboards to execute strategy, optimize business processes, and improve performance. Wayne W. Eckerson (Hingham, MA) is the Director of Research for The Data Warehousing Institute (TDWI), the leading association of business intelligence and data warehousing professionals worldwide that provide high-quality, in-depth education, training, and research. He is a columnist for SearchCIO.com, DM Review, Application Development Trends, the Business Intelligence Journal, and TDWI Case Studies & Solution. |
| data management operating model: 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. |
| data management operating model: Operating Model Canvas (OMC) Mark Lancelott, Mikel Gutierrez, Andrew Campbell, 2017-03-16 The journey from strategy to operating success depends on creating an organization that can deliver the chosen strategy. This book, explaining the Operating Model Canvas, shows you how to do this. It teaches you how to define the main work processes, choose an organization structure, develop a high-level blueprint of the IT systems, decide where to locate and how to lay out floor plans, set up relationships with suppliers and design a management system and scorecard with which to run the new organization. The Operating Model Canvas helps you to create a target operating model aligned to your strategy. The book contains more than 20 examples ranging from large multi-nationals to government departments to small charities and from an operating model for a business to an operating model for a department of five people. The book describes more than 15 tools, including new tools such as the value chain map, the organization model and the high-level IT blueprint. Most importantly, the book contains two fully worked examples showing how the tools can be used to develop a new operating model. This book should be on the desk of every consultant, every strategist, every leader of transformation, every functional business partner, every business or enterprise architect, every Lean expert or business improvement champion, in fact everyone who wants to help their organization be successful. For trainers free additional material of this book is available. This can be found under the Training Material tab. Log in with your trainer account to access the material.Additional content can be found on the website for the Operational Model Canvas: https://www.operatingmodelcanvas.com |
| data management operating model: 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 |
| data management operating model: Networked, Scaled, and Agile Amy Kates, Greg Kesler, Michele DiMartino, 2021-03-03 While technology and geopolitical forces change the face of business today, the patterns and challenges of organizing humans to work together across organization, culture, language and time zone boundaries remain. To face these challenges, all organizations need to be agile, networked and scalable. Networked, Scaled, and Agile reveals how to shape organizations that will enable people to make faster and better decisions in a more complex world. By outlining the tension between the need for agility/differentiation and scale/integration, the book offers a new way to think about this debate using the models of the Tower (vertical integration) and the Square (horizontal integration). It addresses the role of the leadership team and how the organization design process can build C-suite leaders and successors. Each chapter concludes with a series of reflection questions for leaders as well as a summary of key concepts and tips. Including case studies from global organizations, Networked, Scaled, and Agile reveals how organization design can address three of the biggest business challenges organizations face today: how to build a new capability across the entire enterprise; how to make the entire organization more customer-centric; and how to allow for faster innovation. |
| data management operating model: Enterprise Architecture as Strategy Jeanne W. Ross, Peter Weill, David Robertson, 2006 Enterprise architecture defines a firm's needs for standardized tasks, job roles, systems, infrastructure, and data in core business processes. This book explains enterprise architecture's vital role in enabling - or constraining - the execution of business strategy. It provides frameworks, case examples, and more. |
| data management operating model: The Data Model Resource Book, Volume 1 Len Silverston, 2011-08-08 A quick and reliable way to build proven databases for core business functions Industry experts raved about The Data Model Resource Book when it was first published in March 1997 because it provided a simple, cost-effective way to design databases for core business functions. Len Silverston has now revised and updated the hugely successful 1st Edition, while adding a companion volume to take care of more specific requirements of different businesses. This updated volume provides a common set of data models for specific core functions shared by most businesses like human resources management, accounting, and project management. These models are standardized and are easily replicated by developers looking for ways to make corporate database development more efficient and cost effective. This guide is the perfect complement to The Data Model Resource CD-ROM, which is sold separately and provides the powerful design templates discussed in the book in a ready-to-use electronic format. A free demonstration CD-ROM is available with each copy of the print book to allow you to try before you buy the full CD-ROM. |
| data management operating model: The DAMA Dictionary of Data Management Dama International, 2011 A glossary of over 2,000 terms which provides a common data management vocabulary for IT and Business professionals, and is a companion to the DAMA Data Management Body of Knowledge (DAMA-DMBOK). Topics include: Analytics & Data Mining Architecture Artificial Intelligence Business Analysis DAMA & Professional Development Databases & Database Design Database Administration Data Governance & Stewardship Data Management Data Modeling Data Movement & Integration Data Quality Management Data Security Management Data Warehousing & Business Intelligence Document, Record & Content Management Finance & Accounting Geospatial Data Knowledge Management Marketing & Customer Relationship Management Meta-Data Management Multi-dimensional & OLAP Normalization Object-Orientation Parallel Database Processing Planning Process Management Project Management Reference & Master Data Management Semantic Modeling Software Development Standards Organizations Structured Query Language (SQL) XML Development |
| data management operating model: Data Governance: The Definitive Guide Evren Eryurek, Uri Gilad, Valliappa Lakshmanan, Anita Kibunguchy-Grant, Jessi Ashdown, 2021-03-08 As your company moves data to the cloud, you need to consider a comprehensive approach to data governance, along with well-defined and agreed-upon policies to ensure you meet compliance. Data governance incorporates the ways that people, processes, and technology work together to support business efficiency. With this practical guide, chief information, data, and security officers will learn how to effectively implement and scale data governance throughout their organizations. You'll explore how to create a strategy and tooling to support the democratization of data and governance principles. Through good data governance, you can inspire customer trust, enable your organization to extract more value from data, and generate more-competitive offerings and improvements in customer experience. This book shows you how. Enable auditable legal and regulatory compliance with defined and agreed-upon data policies Employ better risk management Establish control and maintain visibility into your company's data assets, providing a competitive advantage Drive top-line revenue and cost savings when developing new products and services Implement your organization's people, processes, and tools to operationalize data trustworthiness. |
| data management operating model: Business Model Management Bernd W. Wirtz, 2020-09-30 “How are business models purposeful designed and structured? How can the models be implemented professionally and managed successfully and sustainably? In what ways can existing business models be adapted to the constantly changing conditions? In this clearly structured reference work, Bernd W. Wirtz gives an answer to all these issues and provides the reader with helpful guidance. Although, ‘Business Model Management’ is first and foremost a scientific reference book, which comprehensively addresses the theory of business models, with his book Bernd W. Wirtz also turns to practitioners. Not least, the many clearly analyzed case studies of companies in different industries contribute to this practical relevance. My conclusion: ‘Business Model Management’ is an informative and worthwhile read, both for students of business administration as a textbook as well as for experienced strategists and decision makers in the company as a fact-rich, practical compendium.” Matthias Müller, Chief Executive Officer Porsche AG (2010-2015), Chief Executive Officer (2015-2018) Volkswagen AG “In dynamic and complex markets a well thought out business model can be a critical factor for the success of a company. Bernd Wirtz vividly conveys how business models can be employed for strategic competition and success analysis. He structures and explains the major theoretical approaches in the literature and practical solutions in an easy and understandable way. Numerous examples from business practice highlight the importance of business models in the context of strategic management. The book has the potential to become a benchmark on the topic business models in the German-speaking world.” Hermann-Josef Lamberti, Member of the Board Deutsche Bank AG 1999-2012/ Member of the Board of Directors, Airbus Group “The business environment has become increasingly complex. Due to changing conditions, the executive board of a company is confronted with growing challenges and increasing uncertainty. Thus, a holistic understanding of the corporate production and performance systems is becoming more and more important. At this point, Bernd W. Wirtz introduces and presents the concept of the structured discussion of the own business model. Business models present operational service processes in aggregated form. This holistic approach channels the attention of management, supports a sound understanding of relationships and facilitates the adaption of the business to changing conditions. The management of business models is thus an integrated management concept. Through the conceptual presentation of complex issues the author makes a valuable contribution to the current literature. In particular, the referenced case studies from various industries make the book clear and very applicable to practice.” Dr. Lothar Steinebach, Member of the Board, Henkel AG 2007-2012/ Supervisory Board, ThyssenKrupp AG |
| data management operating model: Data Governance for Managers Lars Michael Bollweg, 2022-05-13 Professional data management is the foundation for the successful digital transformation of traditional companies. Unfortunately, many companies fail to implement data governance because they do not fully understand the complexity of the challenge (organizational structure, employee empowerment, change management, etc.) and therefore do not include all aspects in the planning and implementation of their data governance. This book explains the driving role that a responsive data organization can play in a company's digital transformation. Using proven process models, the book takes readers from the basics, through planning and implementation, to regular operations and measuring the success of data governance. All the important decision points are highlighted, and the advantages and disadvantages are discussed in order to identify digitization potential, implement it in the company, and develop customized data governance. The book will serve as a useful guide for interested newcomers as well as for experienced managers. |
| data management operating model: Data Governance Success Rupa Mahanti, 2021-12-13 While good data is an enterprise asset, bad data is an enterprise liability. Data governance enables you to effectively and proactively manage data assets throughout the enterprise by providing guidance in the form of policies, standards, processes and rules and defining roles and responsibilities outlining who will do what, with respect to data. While implementing data governance is not rocket science, it is not a simple exercise. There is a lot confusion around what data governance is, and a lot of challenges in the implementation of data governance. Data governance is not a project or a one-off exercise but a journey that involves a significant amount of effort, time and investment and cultural change and a number of factors to take into consideration to achieve and sustain data governance success. Data Governance Success: Growing and Sustaining Data Governance is the third and final book in the Data Governance series and discusses the following: • Data governance perceptions and challenges • Key considerations when implementing data governance to achieve and sustain success• Strategy and data governance• Different data governance maturity frameworks• Data governance – people and process elements• Data governance metrics This book shares the combined knowledge related to data and data governance that the author has gained over the years of working in different industrial and research programs and projects associated with data, processes, and technologies and unique perspectives of Thought Leaders and Data Experts through Interviews conducted. This book will be highly beneficial for IT students, academicians, information management and business professionals and researchers to enhance their knowledge to support and succeed in data governance implementations. This book is technology agnostic and contains a balance of concepts and examples and illustrations making it easy for the readers to understand and relate to their own specific data projects. |
| data management operating model: Competing with High Quality Data Rajesh Jugulum, 2014-03-10 Create a competitive advantage with data quality Data is rapidly becoming the powerhouse of industry, but low-quality data can actually put a company at a disadvantage. To be used effectively, data must accurately reflect the real-world scenario it represents, and it must be in a form that is usable and accessible. Quality data involves asking the right questions, targeting the correct parameters, and having an effective internal management, organization, and access system. It must be relevant, complete, and correct, while falling in line with pervasive regulatory oversight programs. Competing with High Quality Data: Concepts, Tools and Techniques for Building a Successful Approach to Data Quality takes a holistic approach to improving data quality, from collection to usage. Author Rajesh Jugulum is globally-recognized as a major voice in the data quality arena, with high-level backgrounds in international corporate finance. In the book, Jugulum provides a roadmap to data quality innovation, covering topics such as: The four-phase approach to data quality control Methodology that produces data sets for different aspects of a business Streamlined data quality assessment and issue resolution A structured, systematic, disciplined approach to effective data gathering The book also contains real-world case studies to illustrate how companies across a broad range of sectors have employed data quality systems, whether or not they succeeded, and what lessons were learned. High-quality data increases value throughout the information supply chain, and the benefits extend to the client, employee, and shareholder. Competing with High Quality Data: Concepts, Tools and Techniques for Building a Successful Approach to Data Quality provides the information and guidance necessary to formulate and activate an effective data quality plan today. |
| data management operating model: Doing Agile Right Darrell Rigby, Sarah Elk, Steve Berez, 2020-05-26 Agile has the power to transform work--but only if it's implemented the right way. For decades business leaders have been painfully aware of a huge chasm: They aspire to create nimble, flexible enterprises. But their day-to-day reality is silos, sluggish processes, and stalled innovation. Today, agile is hailed as the essential bridge across this chasm, with the potential to transform a company and catapult it to the head of the pack. Not so fast. In this clear-eyed, indispensable book, Bain & Company thought leader Darrell Rigby and his colleagues Sarah Elk and Steve Berez provide a much-needed reality check. They dispel the myths and misconceptions that have accompanied agile's rise to prominence--the idea that it can reshape an organization all at once, for instance, or that it should be used in every function and for all types of work. They illustrate that agile teams can indeed be powerful, making people's jobs more rewarding and turbocharging innovation, but such results are possible only if the method is fully understood and implemented the right way. The key, they argue, is balance. Every organization must optimize and tightly control some of its operations, and at the same time innovate. Agile, done well, enables vigorous innovation without sacrificing the efficiency and reliability essential to traditional operations. The authors break down how agile really works, show what not to do, and explain the crucial importance of scaling agile properly in order to reap its full benefit. They then lay out a road map for leading the transition to a truly agile enterprise. Agile isn't a goal in itself; it's a means to becoming a high-performance operation. Doing Agile Right is a must-have guide for any company trying to make the transition--or trying to sustain high agility. |
| data management operating model: Data Mesh Zhamak Dehghani, 2022-03-08 Many enterprises are investing in a next-generation data lake, hoping to democratize data at scale to provide business insights and ultimately make automated intelligent decisions. In this practical book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today's organizations. A distributed data mesh is a better choice. Dehghani guides architects, technical leaders, and decision makers on their journey from monolithic big data architecture to a sociotechnical paradigm that draws from modern distributed architecture. A data mesh considers domains as a first-class concern, applies platform thinking to create self-serve data infrastructure, treats data as a product, and introduces a federated and computational model of data governance. This book shows you why and how. Examine the current data landscape from the perspective of business and organizational needs, environmental challenges, and existing architectures Analyze the landscape's underlying characteristics and failure modes Get a complete introduction to data mesh principles and its constituents Learn how to design a data mesh architecture Move beyond a monolithic data lake to a distributed data mesh. |
| data management operating model: Data Management at Scale Piethein Strengholt, 2020-07-29 As data management and integration continue to evolve rapidly, storing all your data in one place, such as a data warehouse, is no longer scalable. In the very near future, data will need to be distributed and available for several technological solutions. With this practical book, you’ll learnhow to migrate your enterprise from a complex and tightly coupled data landscape to a more flexible architecture ready for the modern world of data consumption. Executives, data architects, analytics teams, and compliance and governance staff will learn how to build a modern scalable data landscape using the Scaled Architecture, which you can introduce incrementally without a large upfront investment. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including technological developments, regulatory requirements, and privacy concerns Go deep into the Scaled Architecture and learn how the pieces fit together Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata |
| data management operating model: Data Management at Scale Piethein Strengholt, 2023-04-10 As data management continues to evolve rapidly, managing all of your data in a central place, such as a data warehouse, is no longer scalable. Today's world is about quickly turning data into value. This requires a paradigm shift in the way we federate responsibilities, manage data, and make it available to others. With this practical book, you'll learn how to design a next-gen data architecture that takes into account the scale you need for your organization. Executives, architects and engineers, analytics teams, and compliance and governance staff will learn how to build a next-gen data landscape. Author Piethein Strengholt provides blueprints, principles, observations, best practices, and patterns to get you up to speed. Examine data management trends, including regulatory requirements, privacy concerns, and new developments such as data mesh and data fabric Go deep into building a modern data architecture, including cloud data landing zones, domain-driven design, data product design, and more Explore data governance and data security, master data management, self-service data marketplaces, and the importance of metadata |
| data management operating model: Data Management: a gentle introduction Bas van Gils, 2020-03-03 The overall objective of this book is to show that data management is an exciting and valuable capability that is worth time and effort. More specifically it aims to achieve the following goals: 1. To give a “gentle” introduction to the field of DM by explaining and illustrating its core concepts, based on a mix of theory, practical frameworks such as TOGAF, ArchiMate, and DMBOK, as well as results from real-world assignments. 2. To offer guidance on how to build an effective DM capability in an organization.This is illustrated by various use cases, linked to the previously mentioned theoretical exploration as well as the stories of practitioners in the field. The primary target groups are: busy professionals who “are actively involved with managing data”. The book is also aimed at (Bachelor’s/ Master’s) students with an interest in data management. The book is industry-agnostic and should be applicable in different industries such as government, finance, telecommunications etc. Typical roles for which this book is intended: data governance office/ council, data owners, data stewards, people involved with data governance (data governance board), enterprise architects, data architects, process managers, business analysts and IT analysts. The book is divided into three main parts: theory, practice, and closing remarks. Furthermore, the chapters are as short and to the point as possible and also make a clear distinction between the main text and the examples. If the reader is already familiar with the topic of a chapter, he/she can easily skip it and move on to the next. |
| data management operating model: What's Your Digital Business Model? Peter Weill, Stephanie Woerner, 2018-04-17 Digital transformation is not about technology--it's about change. In the rapidly changing digital economy, you can't succeed by merely tweaking management practices that led to past success. And yet, while many leaders and managers recognize the threat from digital--and the potential opportunity--they lack a common language and compelling framework to help them assess it and guide them in responding. They don't know how to think about their digital business model. In this concise, practical book, MIT digital research leaders Peter Weill and Stephanie Woerner provide a powerful yet straightforward framework that has been field-tested globally with dozens of senior management teams. Based on years of study at the MIT Center for Information Systems Research (CISR), the authors find that digitization is moving companies' business models on two dimensions: from value chains to digital ecosystems, and from a fuzzy understanding of the needs of end customers to a sharper one. Looking at these dimensions in combination results in four distinct business models, each with different capabilities. The book then sets out six driving questions, in separate chapters, that help managers and executives clarify where they are currently in an increasingly digital business landscape and highlight what's needed to move toward a higher-value digital business model. Filled with straightforward self-assessments, motivating examples, and sharp financial analyses of where profits are made, this smart book will help you tackle the threats, leverage the opportunities, and create winning digital strategies. |
| data management operating model: Salesforce Data Architecture and Management Ahsan Zafar, 2021-07-30 Learn everything you need to become a successful data architect on the Salesforce platform Key Features Adopt best practices relating to data governance and learn how to implement them Learn how to work with data in Salesforce while maintaining scalability and security of an instance Gain insights into managing large data volumes in Salesforce Book Description As Salesforce orgs mature over time, data management and integrations are becoming more challenging than ever. Salesforce Data Architecture and Management follows a hands-on approach to managing data and tracking the performance of your Salesforce org. You'll start by understanding the role and skills required to become a successful data architect. The book focuses on data modeling concepts, how to apply them in Salesforce, and how they relate to objects and fields in Salesforce. You'll learn the intricacies of managing data in Salesforce, starting from understanding why Salesforce has chosen to optimize for read rather than write operations. After developing a solid foundation, you'll explore examples and best practices for managing your data. You'll understand how to manage your master data and discover what the Golden Record is and why it is important for organizations. Next, you'll learn how to align your MDM and CRM strategy with a discussion on Salesforce's Customer 360 and its key components. You'll also cover data governance, its multiple facets, and how GDPR compliance can be achieved with Salesforce. Finally, you'll discover Large Data Volumes (LDVs) and best practices for migrating data using APIs. By the end of this book, you'll be well-versed with data management, data backup, storage, and archiving in Salesforce. What you will learn Understand the Salesforce data architecture Explore various data backup and archival strategies Understand how the Salesforce platform is designed and how it is different from other relational databases Uncover tools that can help in data management that minimize data trust issues in your Salesforce org Focus on the Salesforce Customer 360 platform, its key components, and how it can help organizations in connecting with customers Discover how Salesforce can be used for GDPR compliance Measure and monitor the performance of your Salesforce org Who this book is for This book is for aspiring architects, Salesforce admins, and developers. You will also find the book useful if you're preparing for the Salesforce Data Architecture and Management exam. A basic understanding of Salesforce is assumed. |
| data management operating model: Data Management courseware based on CDMP Fundamentals Alliance BV And More Group BV, 1970-01-01 Besides the courseware publication (ISBN: 9789401811491), you are advised to obtain the DAMA DMBOK publication (ISBN: 9781634622349). Optionally, you can use the publication Data management: a gentle introduction (ISBN: 9789401805506) as inspiration for examples and quotes about the field of data management. This material is intended to prepare participants for the CDMP exam by DAMA International. The courseware can only be ordered by partners and is based on the current version of the DAMA DMBOK. The material will be updated when new versions of DMBOK are published. DAMA DMBOK is the industry reference for data management. It is published by DAMA International and is currently in its second version. The DMBOK is developed by professionals and can be seen as a collection of best practices. The domain of data management is divided into functional areas which are discussed in terms of definitions (what is it), goals (what are we trying to achieve), steps (what are typical activities), inputs/outputs, and participating roles. Developing and sustaining an effective data management function is far from an easy task. The DMBOK framework is adopted by many organizations as the foundation for their data management function: standardized language and good practices speed up the learning process. After the training, you have an overview of the field of data management, its terminology, and current best practices. |
| data management operating model: Competing in the Age of AI Marco Iansiti, Karim R. Lakhani, 2020-01-07 a provocative new book — The New York Times AI-centric organizations exhibit a new operating architecture, redefining how they create, capture, share, and deliver value. Now with a new preface that explores how the coronavirus crisis compelled organizations such as Massachusetts General Hospital, Verizon, and IKEA to transform themselves with remarkable speed, Marco Iansiti and Karim R. Lakhani show how reinventing the firm around data, analytics, and AI removes traditional constraints on scale, scope, and learning that have restricted business growth for hundreds of years. From Airbnb to Ant Financial, Microsoft to Amazon, research shows how AI-driven processes are vastly more scalable than traditional processes, allow massive scope increase, enabling companies to straddle industry boundaries, and create powerful opportunities for learning—to drive ever more accurate, complex, and sophisticated predictions. When traditional operating constraints are removed, strategy becomes a whole new game, one whose rules and likely outcomes this book will make clear. Iansiti and Lakhani: Present a framework for rethinking business and operating models Explain how collisions between AI-driven/digital and traditional/analog firms are reshaping competition, altering the structure of our economy, and forcing traditional companies to rearchitect their operating models Explain the opportunities and risks created by digital firms Describe the new challenges and responsibilities for the leaders of both digital and traditional firms Packed with examples—including many from the most powerful and innovative global, AI-driven competitors—and based on research in hundreds of firms across many sectors, this is your essential guide for rethinking how your firm competes and operates in the era of AI. |
| data management operating model: Business Relationship Management for the Digital Enterprise Vaughan Philip Merlyn, 2019-08-12 How Business Relationship Management can accelerate time to value in the Digital Enterprise. |
| data management operating model: Data Goverence for the Executive, Orr James C., 2011-01-01 |
| data management operating model: 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. |
| data management operating model: The Case for the Chief Data Officer Peter Aiken, Michael M. Gorman, 2013-04-22 Data are an organization's sole, non-depletable, non-degrading, durable asset. Engineered right, data's value increases over time because the added dimensions of time, geography, and precision. To achieve data's full organizational value, there must be dedicated individual to leverage data as assets - a Chief Data Officer or CDO who's three job pillars are: - Dedication solely to leveraging data assets, - Unconstrained by an IT project mindset, and - Reports directly to the business Once these three pillars are set into place, organizations can leverage their data assets. Data possesses properties worthy of additional investment. Many existing CDOs are fatally crippled, however, because they lack one or more of these three pillars. Often organizations have some or all pillars already in place but are not operating in a coordinated manner. The overall objective of this book is to present these pillars in an understandable way, why each is necessary (but insufficient), and what do to about it. - Uncovers that almost all organizations need sophisticated, comprehensive data management education and strategies. - Delivery of organization-wide data success requires a highly focused, full time Chief Data Officer. - Engineers organization-wide data advantage which enables success in the marketplace |
| data management operating model: EDGE Jim Highsmith, Linda Luu, David Robinson, 2019-08-02 EDGE: The Agile Operating Model That Will Help You Successfully Execute Your Digital Transformation “[The authors’] passion for technology allows them to recognize that for most enterprises in the 21st century, technology is THE business. This is what really separates the EDGE approach. It is a comprehensive operating model with technology at its core.” —From the Foreword by Heidi Musser, Executive Vice President and Principal Consultant, Leading Agile; retired, Vice President and CIO, USAA Maximum innovation happens at the edge of chaos: the messy, risky, and uncertain threshold between randomness and structure. Operating there is uncomfortable but it’s where organizations “invent the future.” EDGE is a set of fast, iterative, adaptive, lightweight, and value-driven tools to achieve digital transformation, and EDGE: Value-Driven Digital Transformation is your guide to using this operating model for innovation. Jim Highsmith is one of the world’s leading agile pioneers and a coauthor of the Agile Manifesto. He, Linda Luu, and David Robinson know from their vast in-the-trenches experience that sustainable digital transformation requires far more than adopting isolated agile practices or conventional portfolio management. This hard, indispensable work involves changing culture and mindset, and going beyond transforming the IT department. EDGE embraces an adaptive mindset in the face of market uncertainty, a visible, value-centered portfolio approach that encourages continual value linkages from vision to detailed initiatives, incremental funding that shifts as strategies evolve, collaborative decision-making, and better risk mitigation. This guide shows leaders how to use the breakthrough EDGE approach to go beyond incremental improvement in a world of exponential opportunities. Build an organization that adapts fast enough to thrive Clear away unnecessary governance processes, obsolete “command and control” leadership approaches, and slow budgeting/planning cycles Improve collaboration when major, fast-paced responses are necessary Continually optimize investment allocation and monitoring based on your vision and goals Register your product for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details. |
| data management operating model: Business Model Pioneers Kai-Ingo Voigt, Oana Buliga, Kathrin Michl, 2016-07-28 Business model innovations are conceived and implemented by a special type of entrepreneur: business model pioneers. This book presents 14 compelling case studies of business model pioneers and their companies, who have successfully introduced new business ideas to the market. The examples range from industries such as retail, media and entertainment to services and industrial projects. For each example, the book provides information on the market environment at the time of launch and illustrates the driving forces behind these business models. Moreover, current market developments are highlighted and linked to the evolution of the business models. Lastly, the authors present the profile of a typical business model pioneer. |
| data management operating model: Traction Gino Wickman, 2012-04-03 OVER 1 MILLION COPIES SOLD! Do you have a grip on your business, or does your business have a grip on you? All entrepreneurs and business leaders face similar frustrations—personnel conflict, profit woes, and inadequate growth. Decisions never seem to get made, or, once made, fail to be properly implemented. But there is a solution. It's not complicated or theoretical.The Entrepreneurial Operating System® is a practical method for achieving the business success you have always envisioned. More than 80,000 companies have discovered what EOS can do. In Traction, you'll learn the secrets of strengthening the six key components of your business. You'll discover simple yet powerful ways to run your company that will give you and your leadership team more focus, more growth, and more enjoyment. Successful companies are applying Traction every day to run profitable, frustration-free businesses—and you can too. For an illustrative, real-world lesson on how to apply Traction to your business, check out its companion book, Get A Grip. |
| data management operating model: Digital Operating Model Rajesh Sinha, 2022-07-26 Build your company’s next-generation growth strategy by using emerging technologies to disrupt your field and energize your business In Digital Operating Model: The Future of Business, digital strategist and execution expert Rajesh Sinha delivers a robust and practical operating blueprint for digital transformation. Applicable to any industry, any size company, this playbook helps executives, professionals, managers, founders, owners, and other business leaders understand the importance and realize the benefits of a digital future for their companies—all without having to spend massive amounts of money in the process. The author explores effective methods to create multiple digital accelerators, develop cultural alignment that fosters innovation and delivers rapid solutions, and shares insights into the new mantras of our goods-and-services on-demand economy. Readers will also find: Step-by-step guidance to implementing a digital platform strategy that leads to exponential business growth Methods for designing and applying new businesses processes that create better experiences internally for your teams and externally for your customers and customers’ customers, which also leads to exponential business growth Real-life examples and case studies of businesses that have achieved successful digital acceleration and grown dramatically in the process Digital Operating Model shows readers how to meet their professional objectives while realizing profound transformation that offers innovative and durable differentiation both in terms of purpose and profits. |
| data management operating model: Super Charge Your Data Warehouse Dan Linstedt, 2011-11-11 Do You Know If Your Data Warehouse Flexible, Scalable, Secure and Will It Stand The Test Of Time And Avoid Being Part Of The Dreaded Life Cycle? The Data Vault took the Data Warehouse world by storm when it was released in 2001. Some of the world's largest and most complex data warehouse situations understood the value it gave especially with the capabilities of unlimited scaling, flexibility and security. Here is what industry leaders say about the Data Vault The Data Vault is the optimal choice for modeling the EDW in the DW 2.0 framework - Bill Inmon, The Father of Data Warehousing The Data Vault is foundationally strong and an exceptionally scalable architecture - Stephen Brobst, CTO, Teradata The Data Vault should be considered as a potential standard for RDBMS-based analytic data management by organizations looking to achieve a high degree of flexibility, performance and openness - Doug Laney, Deloitte Analytics Institute I applaud Dan's contribution to the body of Business Intelligence and Data Warehousing knowledge and recommend this book be read by both data professionals and end users - Howard Dresner, From the Foreword - Speaker, Author, Leading Research Analyst and Advisor You have in your hands the work, experience and testing of 2 decades of building data warehouses. The Data Vault model and methodology has proven itself in hundreds (perhaps thousands) of solutions in Insurance, Crime-Fighting, Defense, Retail, Finance, Banking, Power, Energy, Education, High-Tech and many more. Learn the techniques and implement them and learn how to build your Data Warehouse faster than you have ever done before while designing it to grow and scale no matter what you throw at it. Ready to Super Charge Your Data Warehouse? |
| data management operating model: Exploring the Field of Business Model Innovation Oliver Gassmann, Karolin Frankenberger, Roman Sauer, 2016-10-01 Presenting a broad literature review of scholarly work in the area of Business Model Innovation, this new book analyses 50 management theories in the context of BMI to yield valuable new insights. Research on BMI is still in its infancy and has so far proved to be more than just a sub-discipline of strategy or innovation research. Exploring the field of Business Innovation demonstrates the importance of the discipline as a more specialized management research field and offers new understandings of this important subject. It presents ‘grand theories’ that will help researchers approach BMI through a different angle and describes business models as phenomena, enabling readers to understand their patterns and mechanisms. Reviewing the most important academic work on the subject over the last 15 years, the authors aim to open up the debate and inspire researchers to look at this phenomenon from new and different angles. |
| data management operating model: Enterprise Performance Management Done Right Ron Dimon, 2013-03-06 A workable blueprint for developing and implementing performance management in order to improve revenue growth and profit margins Enterprise performance management (EPM) technology has been rapidly advancing, especially in the areas of predictive analysis and cloud-based solutions. Real Enterprise Performance Management introduces a framework for implementing and managing next-generation functionality for better insight, focus, and alignment of EPM. This blueprint shows that EPM can have a direct positive impact on revenue growth, operating margin, asset utilization, and cash cycle efficiency. Introduces a framework for implementing and managing next-generation functionality for better insight, focus, and alignment Reveals that EPM can have a strong impact on revenue growth, operating margin, asset utilization, cash cycle efficiency Today's businesses have a great deal of data and technology, but less-than-fact decisions are still made. Executives need a structured framework for gathering, analyzing, and debating the best ways to deploy capital, people and time. Real Enterprise Performance Management joins IT and finance in a digestible blueprint for developing and implementing performance management in order to improve revenue growth and profit margins. |
| data management operating model: Designed for Digital Jeanne W. Ross, Cynthia M. Beath, Martin Mocker, 2019-09-24 Practical advice for redesigning “big, old” companies for digital success, with examples from Amazon, BNY Mellon, LEGO, Philips, USAA, and many other global organizations. Most established companies have deployed such digital technologies as the cloud, mobile apps, the internet of things, and artificial intelligence. But few established companies are designed for digital. This book offers an essential guide for retooling organizations for digital success. In the digital economy, rapid pace of change in technology capabilities and customer desires means that business strategy must be fluid. As a result, the authors explain, business design has become a critical management responsibility. Effective business design enables a company to quickly pivot in response to new competitive threats and opportunities. Most leaders today, however, rely on organizational structure to implement strategy, unaware that structure inhibits, rather than enables, agility. In companies that are designed for digital, people, processes, data, and technology are synchronized to identify and deliver innovative customer solutions—and redefine strategy. Digital design, not strategy, is what separates winners from losers in the digital economy. Designed for Digital offers practical advice on digital transformation, with examples that include Amazon, BNY Mellon, DBS Bank, LEGO, Philips, Schneider Electric, USAA, and many other global organizations. Drawing on five years of research and in-depth case studies, the book is an essential guide for companies that want to disrupt rather than be disrupted in the new digital landscape. Five Building Blocks of Digital Business Success: Shared Customer Insights Operational Backbone Digital Platform Accountability Framework External Developer Platform |
| data management operating model: 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. |
| data management operating model: On the Move to Meaningful Internet Systems. OTM 2018 Conferences Hervé Panetto, Christophe Debruyne, Henderik A. Proper, Claudio Agostino Ardagna, Dumitru Roman, Robert Meersman, 2018-10-17 This double volumes LNCS 11229-11230 constitutes the refereed proceedings of the Confederated International Conferences: Cooperative Information Systems, CoopIS 2018, Ontologies, Databases, and Applications of Semantics, ODBASE 2018, and Cloud and Trusted Computing, C&TC, held as part of OTM 2018 in October 2018 in Valletta, Malta. The 64 full papers presented together with 22 short papers were carefully reviewed and selected from 173 submissions. The OTM program every year covers data and Web semantics, distributed objects, Web services, databases, informationsystems, enterprise workflow and collaboration, ubiquity, interoperability, mobility, grid and high-performance computing. |
| data management operating model: Technology Operating Models for Cloud and Edge Ahilan Ponnusamy, Andreas Spanner, 2023-08-11 Align your operating model with your organization's goals and enable leadership, culture, engineering, and operations to tame the complexities of the distributed future Purchase of the print or Kindle book includes a free PDF eBook Key Features Get hands-on with creating your operating model across on-premises, cloud, and edge Learn how to group, construct, and scope operating model dimensions Tackle operating model complexities like architecture, stakeholder management, platform operations, compliance, security, and technology selection Book DescriptionCloud goals, such as faster time to market, lower total cost of ownership (TCO), capex reduction, self-service enablement, and complexity reduction are important, but organizations often struggle to achieve the desired outcomes. With edge computing gaining momentum across industries and making it possible to move workloads seamlessly between cloud and edge locations, organizations need working recipes to find ways of extracting the most value out of their cloud and edge estate. This book provides a practical way to build a strategy-aligned operating model while considering various related factors such as culture, leadership, team structures, metrics, intrinsic motivators, team incentives, tenant experience, platform engineering, operations, open source, and technology choices. Throughout the chapters, you’ll discover how single, hybrid, or multicloud architectures, security models, automation, application development, workload deployments, and application modernization can be reutilized for edge workloads to help you build a secure yet flexible technology operating model. The book also includes a case study which will walk you through the operating model build process in a step-by-step way. By the end of this book, you’ll be able to build your own fit-for-purpose distributed technology operating model for your organization in an open culture way.What you will learn Get a holistic view of technology operating models and linked organization goals, strategy, and teams Overcome challenges of extending tech operating models to distributed cloud and edge environments Discover key architectural considerations in building operating models Explore the benefits of using enterprise-ready open-source products Understand how open hybrid cloud and modern dev and ops practices improve outcomes Who this book is forIf you are a cloud architect, solutions architect, DevSecOps or platform engineering manager, CTO, CIO, or IT decision maker tasked with leading cloud and edge computing initiatives, creating architectures and enterprise capability models, aligning budgets, or showing your board the value of your technology investments, then this book is for you. Prior knowledge of cloud computing, application development, and edge computing concepts will help you get the most out of this book. |
| data management operating model: The Delta Model Arnoldo C. Hax, 2009-11-27 Strategy is the most central issue in management. It has to do with defining the purpose of an organization, understanding the market in which it operates and the capabilities the firm possesses, and putting together a winning plan. There are many influential frameworks to help managers undertake a systematic reflection on this issue. The most dominant approaches are Michael Porter’s Competitive Strategy and the Resource-Based View of the Firm, popularized by Gary Hamel and C.K. Prahalad. Arnoldo Hax argues there are fundamental drawbacks in the underlying hypotheses of these approaches in that they define strategy as a way to achieve sustainable competitive advantage. This line of thinking could be extremely dangerous because it puts the competitor at the center and therefore anchors you in the past, establishes success as a way of beating your competitors, and this obsession often leads toward imitation and congruency. The result is commoditization - which is the worst outcome that could possibly happen to a business. The Delta Model is an extremely innovative view of strategy. It abandons all of these assumptions and instead puts the customer at the center. By doing that it allows us to be truly creative, separating ourselves from the herd in pursuit of a unique and differentiated customer value proposition. Many years of intense research at MIT, supported by an extensive consulting practice, have resulted in development of powerful new concepts and practical tools to guide organizational leaders into a completely different way of looking at strategy, including a new way of doing customer segmentation and examining the competencies of the firm, with an emphasis on using the extended enterprise as a primary way of serving the customer. This last concept means that we cannot play the game alone; that we need to establish a network among suppliers, the firm, the customers, and complementors – firms that are in the business of developing products and services that enhance our own offering to the customer. Illustrated through dozens of examples, and discussion of application to small and medium-sized businesses and not-for-profits, the Delta Model will help readers in all types of organizations break out of old patterns of behavior and achieve strategic flexibility -- an especially timely talent during times of crisis, intense competition, and rapid change. |
| data management operating model: Implementing IT Governance - A Practical Guide to Global Best Practices in IT Management Gad Selig, 2008-04-12 The issues, opportunities and challenges of aligning information technology more closely with an organization and effectively governing an organization s Information Technology (IT) investments, resources, major initiatives and superior uninterrupted service is becoming a major concern of the Board and executive management in enterprises on a global basis. An integrated and comprehensive approach to the alignment, planning, execution and governance of IT and its resources has become critical to more effectively align, integrate, invest, measure, deploy, service and sustain the strategic and tactical direction and value proposition of IT in support of organizations. Much has been written and documented about the individual components of IT Governance such as strategic planning, demand (portfolio investment) management, program and project management, IT service management and delivery, strategic sourcing and outsourcing, performance management and metrics, like the balanced scorecard, compliance and others. Much less has been written about a comprehensive and integrated IT/Business Alignment, Planning, Execution and Governance approach. This new title fills that need in the marketplace and gives readers a structured and practical solutions using the best of the best principles available today. The book is divided into nine chapters, which cover the three critical pillars necessary to develop, execute and sustain a robust and effective IT governance environment - leadership and proactive people and change agents, flexible and scalable processes and enabling technology. Each of the chapters also covers one or more of the following action oriented topics: demand management and alignment (the why and what of IT strategic planning, portfolio investment management, decision authority, etc.); execution management (includes the how - Program/Project Management, IT Service Management with IT Infrastructure Library (ITIL) and Strategic Sourcing and outsourcing); performance, risk and contingency management (e.g. includes COBIT, the balanced scorecard and other metrics and controls); and leadership, teams and people skills. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues …
Belmont Forum Adopts Open Data Principles for Environme…
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to …
Belmont Forum Data Accessibility Statement an…
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
