The Data Management Body of Knowledge (DAMA-DMBOK2) presents a comprehensive view of the challenges, complexities, and value of effective data management.

Today's organizations recognize that managing data is central to their success. They recognize data has value and they want to leverage that value. As our ability and desire to create and exploit data has increased, so too has the need for reliable data management practices.

The second edition of DAMA International's Guide to the Data Management Body of Knowledge updates and augments the highly successful DMBOK1. An accessible, authoritative reference book written by leading thinkers in the field and extensively reviewed by DAMA members, DMBOK2 brings together materials that comprehensively describe the challenges of data management and how to meet them by:

• 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

Chapters include:

• Data Management


• Data Handling Ethics


• Data Governance


• Data Architecture


• Data Modeling and Design


• Data Storage and Operations


• Data Security


• Data Integration & Interoperability


• Document and Content Management


• Reference and Master Data


• Data Warehousing and Business Intelligence


• Metadata Management


• Data Quality Management


• Big Data and Data Science


• Data Management Maturity Assessment


• Data Management Organization and Role Expectations


• Data Management and Organizational Change Management

Standardization of data management disciplines will help data management professionals perform more effectively and consistently. It will also enable organizational leaders to recognize the value and contributions of data management activities.

Enterprise architecture (EA) is a set of descriptions relevant to both business and IT intended to bridge the communication gap between business and IT stakeholders in organizations, facilitate information systems planning and improve business and IT alignment. Due to complex historical reasons, the notion of enterprise architecture was always surrounded by endless speculations, dangerous myths, non-existing best practices, unfulfilled promises, expensive failures and grave disappointments. Traditionally the entire discourse around enterprise architecture was dominated by shallow advice and faddish approaches (e.g. well-known EA frameworks) infinitely distant from the practical realities, but nonetheless aggressively promoted by commercially motivated consultancies and gurus. At the same time, realistic and trustworthy information on enterprise architecture is still incredibly hard to find in any available sources.

Based on an extensive study of the actual industry best practices and existing EA literature, this book provides a unique, systematic, end-to-end description of various aspects of an EA practice integrated into a consistent logical picture. In particular, this book offers clear, research-based, conceptually sound and practically actionable answers to the key questions related to enterprise architecture:

• What is the meaning of enterprise architecture and an EA practice?
• What processes constitute established EA practices and how do they work?
• What EA artifacts are used in successful EA practices and how?
• What is the best way to structure architecture roles and functions?
• What software tools and modeling languages are necessary for enterprise architecture?
• How to initiate an EA practice in organizations from scratch and evolve it?
• Where do current EA best practices originate from?

This book is organized in a highly structured, sequential manner and does not require any prior knowledge of enterprise architecture. The book is intended for a broad audience of people interested in enterprise architecture including practicing and aspiring architects, architecture managers, academic EA researchers, EA lecturers and students in universities.

La Guía del Conocimiento para la Gestión de Datos (DAMA-DMBOK2) presenta una visión exhaustiva de los desafíos, complejidades y valor de la gestión eficaz de los datos.

Las organizaciones de hoy en día reconocen que la gestión de los datos es fundamental para su éxito. Reconocen que los datos tienen valor y quieren aprovechar ese valor. A medida que nuestra capacidad y deseo de crear y explotar datos ha aumentado, también lo ha hecho la necesidad de prácticas de gestión de datos confiables.

La segunda edición de la Guía del Conocimiento para la Gestión de Datos de DAMA International actualiza y aumenta el exitoso DMBOK1. DMBOK2, un libro de referencia accesible y autorizado, escrito por los principales pensadores en el campo y ampliamente revisado por los miembros de DAMA, reúne materiales que describen exhaustivamente los desafíos de la gestión de datos y cómo cumplirlos mediante:

- Definir un conjunto de principios rectores para la gestión de datos y describir cómo se pueden aplicar estos principios dentro de las áreas funcionales de gestión de datos.

- Proporcionar un marco de referencia funcional para la implementación de prácticas de gestión de datos empresariales, incluyendo prácticas, métodos y técnicas ampliamente adoptadas, funciones, roles, entregables y métricas.

- Establecer un vocabulario común para los conceptos de gestión de datos y servir de base para las mejores prácticas para los profesionales de la gestión de datos.

Enterprise architecture (EA) is a set of descriptions relevant to both business and IT intended to bridge the communication gap between business and IT stakeholders in organizations, facilitate information systems planning and improve business and IT alignment. Due to complex historical reasons, the notion of enterprise architecture was always surrounded by endless speculations, dangerous myths, non-existing best practices, unfulfilled promises, expensive failures and grave disappointments. Traditionally the entire discourse around enterprise architecture was dominated by shallow advice and faddish approaches (e.g. well-known EA frameworks) infinitely distant from the practical realities, but nonetheless aggressively promoted by commercially motivated consultancies and gurus. At the same time, realistic and trustworthy information on enterprise architecture is still incredibly hard to find in any available sources.

Based on an extensive study of the actual industry best practices and existing EA literature, this book provides a unique, systematic, end-to-end description of various aspects of an EA practice integrated into a consistent logical picture. In particular, this book offers clear, research-based, conceptually sound and practically actionable answers to the key questions related to enterprise architecture:

• What is the meaning of enterprise architecture and an EA practice?
• What processes constitute established EA practices and how do they work?
• What EA artifacts are used in successful EA practices and how?
• What is the best way to structure architecture roles and functions?
• What software tools and modeling languages are necessary for enterprise architecture?
• How to initiate an EA practice in organizations from scratch and evolve it?
• Where do current EA best practices originate from?

This book is organized in a highly structured, sequential manner and does not require any prior knowledge of enterprise architecture. The book is intended for a broad audience of people interested in enterprise architecture including practicing and aspiring architects, architecture managers, academic EA researchers, EA lecturers and students in universities.

Enterprise architects are specialized industry professionals responsible for leading joint business and IT planning in organizations, thereby enabling the success of their digital transformation efforts. Despite their immediate relevance to today's ubiquitous digitalization tendencies, the very presence of enterprise architects, as unique organizational characters, is largely unnoticed in the mainstream discourse and their role undeservingly remains in the shadow. Even though enterprise architects have existed, in some form, since the dawn of business computing, no comprehensive information sources devoted specifically to their profession have been created so far. Whereas the broader phenomenon of enterprise architecture enjoyed significant attention in the industry, the central actors of the respective practices themselves relatively rarely became the subject of discussion, as if their behavior and activities are self-evident.

Based on an extensive study of the work of enterprise architects and the existing topical literature, this book provides the first detailed and systematic description of various aspects of their occupation integrated into a coherent logical picture. In particular, this book offers clear, research-based, conceptually sound and practically actionable answers to the key questions about enterprise architects:

Who are enterprise architects as personalities and what do they do?What knowledge, skills and experience do enterprise architects possess?What kind of instruments do enterprise architects employ?What activities do enterprise architects perform and how do these activities compose their work in organizations?What types and specializations of architects exist and how do they differ?What challenges do enterprise architects face in their job and how can they be overcome?What should one do to become an enterprise architect in the future?

This book is organized in a highly structured, sequential manner and does not require any prior acquaintance with the trade of enterprise architects. The book is intended for a broad audience of people interested in enterprise architects including aspiring and experienced practitioners, architecture managers, academic researchers, lecturers and students in universities.

If you are leading an organization or if you need to communicate with leaders about data management, Navigating the Labyrinth is your guide.

Organizations that want to get value from their data need to manage that data well. But to most executives, data management seems obscure, complicated, and highly technical. You don't have time to learn all the detail or cut through the hype. Navigating the Labyrinth helps you get there. Based on best practices from DAMA's Data Management Body of Knowledge (DMBOK2), it explains the fundamentals and says why they are important. It focuses your attention on what you need to know to help your organization build trust in and get value out of its data.

La estrategia es la clave para ganar cualquier juego, y la Estrategia de Datos es la clave para ganar el juego de la Gestión de Datos. La Estrategia de Datos es un concepto en plural, ya que comprende un conjunto de diferentes estrategias interrelacionadas que trabajan juntas para cumplir con los objetivos estratégicos de negocio y las necesidades de datos del negocio y resolver los puntos de dolor de datos de una organización. Las Estrategias de Datos ayudan a gestionar las expectativas de lo que está sucediendo en el ámbito de los datos. Describirlas es un arte. Por lo tanto, se necesita un lienzo para capturarlas y comunicarlas. Este libro te muestra cuáles deberían ser esas estrategias constituyentes y qué se incluye en sus lienzos. Es una guía completa que lo llevará paso a paso sobre cómo producir una Estrategia de Datos a nivel empresarial. Si sigue estos consejos, tendrá una Estrategia de Datos práctica, ágil y fácil de comunicar (PAC) para mantener a sus equipos y organización alineados.

Todos sabemos que los datos desempeñarán un papel cada vez más importante en todas las operaciones futuras. La forma en que usted y su organización apliquen los datos a las operaciones será la diferencia entre el éxito y el fracaso. Después de haber trabajado en esta área durante muchos años, ha llegado el momento de dar el siguiente paso en la evolución de la estrategia de datos. Marilú ha dado este paso. Como entusiasta adherente a la técnica del lienzo de negocio (business canvas), admiro mucho la diligencia con la que ha aplicado esto al concepto de formulación de una estrategia de datos. Hay una gran cantidad de material en este libro muy denso de consejos, técnicas y orientación extremadamente útiles. Probablemente, el aspecto más difícil de la formulación de la estrategia de datos se centra en el desafío de involucrar de manera significativa a varias partes interesadas en los diálogos necesarios para tomar los datos de su organización y aplicarlos de manera significativa en apoyo de la estrategia organizacional. El método descrito proporciona toda la orientación que necesitará.

Este es un libro completo sobre estrategias de datos. Marilú López ha ideado una forma de conectar la estrategia de datos con la gestión ejecutiva que hasta ahora ha sido una pieza que faltaba; cómo poner en marcha las estrategias de datos. No se limita a abordar el proceso de crear una estrategia de datos como si fuera un pastel para hornear. En cambio, hace que el lector piense en qué tipo de estrategias de datos se necesitan y cómo encajan en los desafíos, intenciones y aspiraciones de su organización. El contenido es muy creíble ya que Marilú López utiliza y se relaciona constantemente con la investigación académica, la literatura y las experiencias de los líderes de opinión. Por lo tanto, su marco PAC se basa en el conocimiento acumulado de hoy y lo lleva más lejos desde allí. Si está a punto de emprender un trabajo de estrategia de datos, debe empezar por revisar primero los mensajes de Marilú López.

Understand the full range of systems approaches and how to use them with this innovative overview.

Leaders and managers face increasing complexity and uncertainty because technical, organizational, socio-cultural, political, and environmental issues have become intensely interconnected. Systems thinking is recognized as the essential competence for managing complexity. As the demand for systems thinking grows, however, the fragmentation of the field into different methodologies has become a potential liability. Critical systems thinking (CST) shows how this diversity can be a strength rather than a weakness by revealing how different systems methodologies address various aspects of complexity and how they can be used in combination to resolve the messiest of wicked problems.

Critical Systems Thinking offers, in a single volume, an account of the value of systems thinking and CST in the modern world, an explanation of the pragmatic philosophy and expansion in mindset necessary to embrace CST, and detailed instructions on how to undertake critical systems practice (CSP) using the variety of systems approaches to navigate multi-dimensional complexity.

Readers will find:

• An accessible introduction to systems thinking and CST.
• A description and critique of the best-known systems methodologies.
• A guide to the mindset changes, the steps required, and the toolkit necessary to undertake successful CSP.
• Case studies and examples of CSP.
• A discussion of the nature of systemic leadership.

Critical Systems Thinking is ideal for leaders and managers in government, business, the public sector, the professions, and beyond who want to understand the potential of systems thinking and use it in their work. It is essential for systems researchers and practitioners who want a deeper understanding of the field.

Enterprise architecture (EA) is a set of descriptions relevant to both business and IT intended to bridge the communication gap between business and IT stakeholders in organizations, facilitate information systems planning and improve business and IT alignment. Due to complex historical reasons, the notion of enterprise architecture was always surrounded by endless speculations, dangerous myths, non-existing best practices, unfulfilled promises, expensive failures and grave disappointments. Traditionally the entire discourse around enterprise architecture was dominated by shallow advice and faddish approaches (e.g. well-known EA frameworks) infinitely distant from the practical realities, but nonetheless aggressively promoted by commercially motivated consultancies and gurus. At the same time, realistic and trustworthy information on enterprise architecture is still incredibly hard to find in any available sources.

Based on an extensive study of the actual industry best practices and existing EA literature, this book provides a unique, systematic, end-to-end description of various aspects of an EA practice integrated into a consistent logical picture. In particular, this book offers clear, research-based, conceptually sound and practically actionable answers to the key questions related to enterprise architecture:

• What is the meaning of enterprise architecture and an EA practice?
• What processes constitute established EA practices and how do they work?
• What EA artifacts are used in successful EA practices and how?
• What is the best way to structure architecture roles and functions?
• What software tools and modeling languages are necessary for enterprise architecture?
• How to initiate an EA practice in organizations from scratch and evolve it?
• Where do current EA best practices originate from?

This book is organized in a highly structured, sequential manner and does not require any prior knowledge of enterprise architecture. The book is intended for a broad audience of people interested in enterprise architecture including practicing and aspiring architects, architecture managers, academic EA researchers, EA lecturers and students in universities.

Imagine spending a day with top analytical leaders and asking any question you want. In this book, Wayne Eckerson illustrates analytical best practices by weaving his perspective with commentary from seven directors of analytics who unveil their secrets of success. With an innovative flair, Eckerson tackles a complex subject with clarity and insight. Each of the book's 20 chapters is a stand-alone essay on an analytical topic, yet collectively they form a concise methodology about how to implement a successful analytics program.

From the Foreword by Michael Halbherr, Executive Vice President, Nokia

We are living in a time of radical change. From my vantage point as head of Nokia's Location and Commerce business, I see many business and technical trends shaping our future--and all depend on a new commodity: data. In our mapping business, I see the need to evolve from a road-centric tool to something that allows people to truly understand and maneuver the complexities of a modern city. To accomplish this, we need a lot of data and ways to correlate disparate information into what we call Smart Data. Analytics is core to what we do, and how we deliver value to customers today and in the future.

I recently spoke to the Nokia board about our data, and some members questioned how we could monetize this asset. Since a few members are executives in the oil industry, I told them that data is the oil of the future, and that you monetize this new resource the same way you monetize oil, by spending time and money refining it. In our case, we are refining data about people, locations, social interactions, traffic, musical preferences, and so on to bring maps to life.

The analytical leaders profiled in this book demonstrate how to refine data for business gain and innovation. They play a pivotal role by bridging the worlds of business and technology. When supported by the business, they've delivered remarkable solutions that have given their organizations a competitive edge.

I highly recommend this book to anyone who wants to monetize the most important resource of our time: data. It's written in language that both a CEO and a CIO can understand, and carries important lessons no matter what side of the business-technology aisle someone sits.

Enterprise architecture (EA) is a set of descriptions relevant to both business and IT intended to bridge the communication gap between business and IT stakeholders in organizations, facilitate information systems planning and improve business and IT alignment. Due to complex historical reasons, the notion of enterprise architecture was always surrounded by endless speculations, dangerous myths, non-existing best practices, unfulfilled promises, expensive failures and grave disappointments. Traditionally the entire discourse around enterprise architecture was dominated by shallow advice and faddish approaches (e.g. well-known EA frameworks) infinitely distant from the practical realities, but nonetheless aggressively promoted by commercially motivated consultancies and gurus. At the same time, realistic and trustworthy information on enterprise architecture is still incredibly hard to find in any available sources.

Based on an extensive study of the actual industry best practices and existing EA literature, this book provides a unique, systematic, end-to-end description of various aspects of an EA practice integrated into a consistent logical picture. In particular, this book offers clear, research-based, conceptually sound and practically actionable answers to the key questions related to enterprise architecture:

• What is the meaning of enterprise architecture and an EA practice?
• What processes constitute established EA practices and how do they work?
• What EA artifacts are used in successful EA practices and how?
• What is the best way to structure architecture roles and functions?
• What software tools and modeling languages are necessary for enterprise architecture?
• How to initiate an EA practice in organizations from scratch and evolve it?
• Where do current EA best practices originate from?

This book is organized in a highly structured, sequential manner and does not require any prior knowledge of enterprise architecture. The book is intended for a broad audience of people interested in enterprise architecture including practicing and aspiring architects, architecture managers, academic EA researchers, EA lecturers and students in universities.

Get peak performance from your SAP ERP infrastructure using the detailed implementation, maintenance, and support information in this comprehensive resource. SAP Basis Administration Handbook, NetWeaver Edition delivers integrated management strategies covering both ABAP and Java stacks. Discover how to deploy components, accurately size throughout, configure Oracle databases, back up your system, and repair performance problems. Career trends, certification requirements, and marketable SAP Basis skills are also discussed in this practical guide.

Essential Skills for SAP Professionals:

• Plan, prepare, and install SAP NetWeaver Application Server
• Set up, configure, and troubleshoot Java and ABAP stacks
• Establish server infrastructure and efficiently balance workloads
• Incorporate transport management and software logistics
• Resolve performance issues and startup problems
• Access SAP support infrastructure through SAP Service Marketplace
• Manage and back up Oracle databases using BR*TOOLS
• Perform system copies, stack upgrades, and OS/DB migrations

Complete and comprehensive manual for eliciting, defining, and managing needs and requirements, integration, verification, and validation across the lifecycle

The INCOSE Needs and Requirements Manual presents product development and systems engineering practices, activities, and artifacts from the perspective of needs, requirements, verification, and validation across the system lifecycle. Composed of 16 chapters, this book provides practical guidance to help organizations understand the importance of lifecycle concepts, needs, requirements, verification, and validation activities, enabling them to successfully and effectively implement these activities during product development, systems engineering, and project management.

The parent handbook published by Wiley, INCOSE Systems Engineering Handbook, divides the system lifecycle into a series of processes, with each process described in terms of a series of activities. This Manual provides more detail needed by practitioners to successfully implement these activities, with guidance and lessons learned from hundreds of years of collective experience of the authors, contributors, and reviewers. For example, while the Handbook mentions the need to define the problem statement, mission, goals, and objectives for a system, the Manual provides detailed guidance on doing so.

Sample topics covered in the INCOSE Needs and Requirements Manual include:

• Defining the problem, opportunity, or threat and defining a mission statement, goals, objectives, and measures.
• Identifying external and internal stakeholders, eliciting stakeholder needs and requirements, defining drivers and constraints, and assessing risk.
• Performing lifecycle concept analysis and maturation and defining an integrated set of needs that represents the scope of the project.
• Transforming the integrated set of needs into well-formed design input requirements.
• Using attributes to manage needs and requirements across the lifecycle.
• Continuous integration, verification, and validation across the lifecycle.
• Moving between levels of the architecture, flow down and allocation of requirements, and budgeting performance, resource, and quality requirements.
• Defining the system verification and system validation success criteria, method, strategy, and responsible organizations.
• Planning and executing successful system verification and validation programs.
• Managing needs, requirements, verification, and validation across the lifecycle.
• Understanding the importance of an integrated, collaborative project team and effective communication between team members

TheINCOSE Needs and Requirements Manual is an essential accompanying reference to the INCOSE Systems Engineering Handbook for novice and seasoned system engineers, software engineers, project managers, product developers, tool vendors, course developers, educators, trainers, customers, suppliers, non-SE stakeholders, as well as researchers and students studying systems engineering and systems design.

Strategy is the key to winning any game, and Data Strategy is the key to winning the Data Management game. Data Strategy is a concept in the plural, as it comprises a set of different interrelated strategies that work together to meet business strategic objectives and business data needs and solve an organization's data pain points. Data Strategies help manage expectations of what is happening in the data arena. Describing them is an art. Thus, a canvas is needed to capture and communicate them. This book shows you what those constituent strategies should be and what goes into their canvases. It is a comprehensive guide that will take you step by step on how to produce an Enterprise Level Data Strategy. If you follow this advice, you will have a practical, agile, and easy-to-communicate (PAC) Data Strategy to keep your teams and organization aligned.

We all know that data will play an increasingly important role in all future operations. How you personally and your organization apply data to operations will be the difference between success and failure. Have worked in this area for many years, the time is ripe for the next step in the evolution of data strategy. Marilu has taken this step. As an enthusiastic adherent to the business canvas technique, I greatly admire the diligence with which she has applied this to the concept of formulating a data strategy. There is a wealth of material in this very dense book of extremely useful tips, techniques, and guidance. Probably the most difficult aspect of data strategy formulation centers on the challenge of meaningfully engaging various stakeholders in the necessary dialogs required to take your organizations data and applying it meaningfully in support of the organizational strategy. The method described provides all the guidance you will need.

This is a comprehensive book on data strategies. Marilu Lopez has come up with a way to connect the data strategy to executive management that until now has been a missing piece; how to set the data strategies in motion. She doesn't just go into how to create a data strategy as if it were a cake to be baked. Instead, she makes the reader think about what kind of data strategies are needed and how they fit into your organization's challenges, intentions, and aspirations. The content is very credible as Marilu Lopez consistently uses and relates to academic research, literature, and thought leaders' experiences. Thus, her PAC framework is based on today's accumulated knowledge and takes you further from there. If you are about to take on data strategy work, you should start by first checking out Marilu Lopez's messages.

Today's college graduates think that technology is all about choosing a technology or a technology stack in order to get work done. They don't see that there is a larger infrastructure that they are a part of. What is needed is a book on the larger concepts that shape the IT industry. I recommend the book by Marilu Lopez as a starting place for understanding the larger framework under which IT operates.

Unlock the Full Potential of Enterprise AI

Artificial Intelligence (AI) is transforming industries, but how can enterprises truly harness its power to drive real business value? AI: Achieving Impact presents a practical, structured approach to integrating AI into business operations using the AI Factory framework. Written by industry expert John Napoli, this book provides executives, AI leaders, and business strategists with a clear roadmap for successful AI adoption.

✅ The AI Factory Approach - Learn how to build a systematic, scalable AI strategy that aligns with business goals.
✅ GenAI vs. Traditional AI - Understand the fundamental differences and how to leverage both for maximum impact.
✅ AI Investment & Prioritization - Identify high-value AI use cases, optimize funding strategies, and measure ROI effectively.
✅ Data Governance & Security - Ensure AI success with a strong data foundation, compliance, and ethical safeguards.
✅ Talent & Organizational Readiness - Discover strategies for reskilling the workforce and fostering a digital-first culture.
✅ Real-World Case Studies - Explore applied examples, including Microsoft Copilots, AI in banking, and Fortune 250 transformations.

Whether you're an AI visionary, a C-level leader, or an organization looking to accelerate digital transformation, AI: Achieving Impact provides actionable insights to help you move beyond the hype and achieve real-world results.