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| cmmi data management maturity model: CMMI Ralf Kneuper, 2009 CMMI is a well-known and standardized model for assessing and improving software and systems development processes. It can be used to guide process improvement across a project, a division, or an entire organization. CMMI was developed at the Carnegie Mellon Software Engineering Institute (SEI). The current version, 1.2, was published in 2006 and is being adopted worldwide. This book provides hands-on experience and will help the reader to gain an understanding of CMMI. It is an introduction to the model and its fundamental ideas. Through numerous examples, it helps the reader to get started with CMMI and to understand the interrelationship among model components (practices, goals, and process areas). The book covers the following topics: Model-based process improvement Overview of CMMI components History of CMMI and comparison to CMM Process areas of CMMI models Application, potential, and limitations of CMMI |
| cmmi data management maturity 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. |
| cmmi data management maturity model: The "Orange" Model of Data Management Irina Steenbeek, 2019-10-21 *This book is a brief overview of the model and has only 24 pages.*Almost every data management professional, at some point in their career, has come across the following crucial questions:1. Which industry reference model should I use for the implementation of data managementfunctions?2. What are the key data management capabilities that are feasible and applicable to my company?3. How do I measure the maturity of the data management functions and compare that withthose of my peers in the industry4. What are the critical, logical steps in the implementation of data management?The Orange (meta)model of data management provides a collection of techniques and templates for the practical set up of data management through the design and implementation of the data and information value chain, enabled by a set of data management capabilities.This book is a toolkit for advanced data management professionals and consultants thatare involved in the data management function implementation.This book works together with the earlier published The Data Management Toolkit. The Orange model assists in specifying the feasible scope of data management capabilities, that fits company's business goals and resources. The Data Management Toolkit is a practical implementation guide of the chosen data management capabilities. |
| cmmi data management maturity model: CMMI for Acquisition Brian Gallagher, Mike Phillips, Karen Richter, Sandra Shrum, 2011-03-04 CMMI® for Acquisition (CMMI-ACQ) describes best practices for the successful acquisition of products and services. Providing a practical framework for improving acquisition processes, CMMI-ACQ addresses the growing trend in business and government for organizations to purchase or outsource required products and services as an alternative to in-house development or resource allocation. Changes in CMMI-ACQ Version 1.3 include improvements to high maturity process areas, improvements to the model architecture to simplify use of multiple models, and added guidance about using preferred suppliers. CMMI® for Acquisition, Second Edition, is the definitive reference for CMMI-ACQ Version 1.3. In addition to the entire revised CMMI-ACQ model, the book includes updated tips, hints, cross-references, and other author notes to help you understand, apply, and quickly find information about the content of the acquisition process areas. The book now includes more than a dozen contributed essays to help guide the adoption and use of CMMI-ACQ in industry and government. Whether you are new to CMMI models or are already familiar with one or more of them, you will find this book an essential resource for managing your acquisition processes and improving your overall performance. The book is divided into three parts. Part One introduces CMMI-ACQ in the broad context of CMMI models, including essential concepts and useful background. It then describes and shows the relationships among all the components of the CMMI-ACQ process areas, and explains paths to the adoption and use of the model for process improvement and benchmarking. Several original essays share insights and real experiences with CMMI-ACQ in both industry and government environments. Part Two first describes generic goals and generic practices, and then details the twenty-two CMMI-ACQ process areas, including specific goals, specific practices, and examples. These process areas are organized alphabetically and are tabbed by process area acronym to facilitate quick reference. Part Three provides several useful resources, including sources of further information about CMMI and CMMI-ACQ, acronym definitions, a glossary of terms, and an index. |
| cmmi data management maturity model: IQM-CMM: Information Quality Management Capability Maturity Model Sasa Baskarada, 2010-04-03 Saša Baškarada presents a capability maturity model for information quality management process assessment and improvement. The author employed six exploratory case studies and a four round Delphi study to gain a better understanding of the research problem and to build the preliminary model, which he then applied in seven international case studies for further enhancement and external validation. |
| cmmi data management maturity model: Modern Data Strategy Mike Fleckenstein, Lorraine Fellows, 2018-02-12 This book contains practical steps business users can take to implement data management in a number of ways, including data governance, data architecture, master data management, business intelligence, and others. It defines data strategy, and covers chapters that illustrate how to align a data strategy with the business strategy, a discussion on valuing data as an asset, the evolution of data management, and who should oversee a data strategy. This provides the user with a good understanding of what a data strategy is and its limits. Critical to a data strategy is the incorporation of one or more data management domains. Chapters on key data management domains—data governance, data architecture, master data management and analytics, offer the user a practical approach to data management execution within a data strategy. The intent is to enable the user to identify how execution on one or more data management domains can help solve business issues. This book is intended for business users who work with data, who need to manage one or more aspects of the organization’s data, and who want to foster an integrated approach for how enterprise data is managed. This book is also an excellent reference for students studying computer science and business management or simply for someone who has been tasked with starting or improving existing data management. |
| cmmi data management maturity model: CMMI Distilled Dennis M. Ahern, Aaron Clouse, Richard Turner, 2004 This edition is especially appropriate for executives and managers who need to understand why process improvement is valuable, why CMMI is a tool of choice, and how to maximize the return on their efforts and investments. |
| cmmi data management maturity model: Stakeholder Relationship Management Lynda Bourne, 2016-04-01 In any activity an organisation undertakes, whether strategic, operational or tactical, the activity can only be successful with the input, commitment and support of its people - stakeholders. Gaining and maintaining the support and commitment of stakeholders requires a continuous process of engaging the right stakeholders at the right time and understanding and managing their expectations. Unfortunately, most organisations have difficulty implementing such culture change, and need assistance and guidance to implement a consistent process for identification and management of stakeholders and their changing expectations. As a continuous improvement process, stakeholder management requires understanding and support from everyone in the organisation from the CEO to the short-term contractor. This requires the concepts and practices of effective stakeholder management to become embedded in the culture of the organisation: 'how we do things around here', this book provides the 'road map' to help organisations achieve these objectives. The text has two specific purposes. Firstly, it is an 'how-to' book providing the fundamental processes and practices for improving stakeholder management in endeavours such as projects, and program management offices (PMO), it also gives guidance on organisational survival during mergers and acquisitions, preparing for the tender bidding, and marketing campaigns. Secondly, Lynda Bourne's book is for organisations that have recognised the importance of stakeholder engagement to their success, it is a guidebook for assessing their current maturity regarding implementation of stakeholder relationship management with a series of guidelines and milestones for achieving the preferred level of maturity. |
| cmmi data management maturity model: Data Governance Dimitrios Sargiotis, |
| cmmi data management maturity model: Business Process Maturity Amy Van Looy, 2014-01-27 Organisations face many challenges, which induce them to perform better, and thus to establish mature (or excellent) business processes. As they now face globalisation, higher competitiveness, demanding customers, growing IT possibilities, compliancy rules etc., business process maturity models (BPMMs) have been introduced to help organisations gradually assess and improve their business processes (e.g. CMMI or OMG-BPMM). In fact, there are now so many BPMMs to choose from that organisations risk selecting one that does not fit their needs or one of substandard quality. This book presents a study that distinguishes process management from process orientation so as to arrive at a common understanding. It also includes a classification study to identify the capability areas and maturity types of 69 existing BPMMs, in order to strengthen the basis of available BPMMs. Lastly it presents a selection study to identify criteria for choosing one BPMM from the broad selection, which produced a free online selection tool, BPMM Smart-Selector. |
| cmmi data management maturity model: Data Governance and Strategies Mr.Desidi Narsimha Reddy, 2024-09-05 Mr.Desidi Narsimha Reddy, Data Consultant (Data Governance, Data Analytics: Enterprise Performance Management, AI & ML), Soniks consulting LLC, 101 E Park Blvd Suite 600, Plano, TX 75074, United States. |
| cmmi data management maturity model: The Capability Maturity Model Mark C. Paulk, 1995 Principal Contributors and Editors: Mark C. Paulk, Charles V. Weber, Bill Curtis, Mary Beth Chrissis In every sense, the CMM represents the best thinking in the field today... this book is targeted at anyone involved in improving the software process, including members of assessment or evaluation teams, members of software engineering process groups, software managers, and software practitioners... From the Foreword by Watts Humphrey The Capability Maturity Model for Software (CMM) is a framework that demonstrates the key elements of an effective software process. The CMM describes an evolutionary improvement path for software development from an ad hoc, immature process to a mature, disciplined process, in a path laid out in five levels. When using the CMM, software professionals in government and industry can develop and improve their ability to identify, adopt, and use sound management and technical practices for delivering quality software on schedule and at a reasonable cost. This book provides a description and technical overview of the CMM, along with guidelines for improving software process management overall. It is a sequel to Watts Humphrey's important work, Managing the Software Process, in that it structures the maturity framework presented in that book more formally. Features: Compares the CMM with ISO 9001 Provides an overview of ISO's SPICE project, which is developing international standards for software process improvement and capability determination Presents a case study of IBM Houston's Space Shuttle project, which is frequently referred to as being at Level 5 0201546647B04062001 |
| cmmi data management maturity model: Data Integrity and Data Governance R. D. McDowall, 2018-11-09 This book provides practical and detailed advice on how to implement data governance and data integrity for regulated analytical laboratories working in the pharmaceutical and allied industries. |
| cmmi data management maturity model: The Data Science Framework Juan J. Cuadrado-Gallego, Yuri Demchenko, 2020-10-01 This edited book first consolidates the results of the EU-funded EDISON project (Education for Data Intensive Science to Open New science frontiers), which developed training material and information to assist educators, trainers, employers, and research infrastructure managers in identifying, recruiting and inspiring the data science professionals of the future. It then deepens the presentation of the information and knowledge gained to allow for easier assimilation by the reader. The contributed chapters are presented in sequence, each chapter picking up from the end point of the previous one. After the initial book and project overview, the chapters present the relevant data science competencies and body of knowledge, the model curriculum required to teach the required foundations, profiles of professionals in this domain, and use cases and applications. The text is supported with appendices on related process models. The book can be used to develop new courses in data science, evaluate existing modules and courses, draft job descriptions, and plan and design efficient data-intensive research teams across scientific disciplines. |
| cmmi data management maturity model: CMMI Mary Beth Chrissis, Mike Konrad, Sandy Shrum, 2007 Updated revision of the best selling book on CMMI – now covering version 1.2. |
| cmmi data management maturity model: Data Management Fundamentals (DMF) - CDMP exam preparation Paul Rakké, 1970-01-01 Besides this Data Management Fundamentals (DMF) CDMP exam preparation book, you are advised to obtain the publication the Data Management courseware based on CDMP Fundamentals - Revised edition (ISBN: 9789401811491) for your preparation for your Certified Data Management Professional (CDMP) certification. This CDMP certification based on the DAMA DMBok (Data Management Body of Knowledge) is a globally recognized credential that validates the knowledge and skills required in the field of data management.This exam preparation book is a well-balanced guide to help you pass the CDMP exam and earn your certification. All the knowledge areas as described in the related courseware and/or DAMA-DMBOK (2nd edition) of the well-known study book plus extra topics as described in the book too, will be treated with exam-like questions. The number of questions per topic can differ, depending on the weights as used in the formal exam composition. All the questions are newly defined questions by the author. Separately the correct answers and guiding explanations with references to the DAMA-DMBOK book are provided. Besides the set of questions per topic which consist of a set of 140 questions, also a set of 100 extra questions with the same weights per topic is provided to give you the opportunity to prepare yourself on the exam with this similar exam. So this 240 new questions provided in this book make your road to the CDMP certification complete. |
| cmmi data management maturity model: CMMI Scampi Distilled Dennis M. Ahern, 2005 Part of The SEI Series in Software Engineering, this book offers a concise andpractical guide to the standard CMMI appraisal method. This method is veryimportant, as it is used to determine an organization's capability and maturitylevels (which are often used as criteria in awarding government and defenseorientedbids). SCAMPI specifically stands for: The Standard CMMI AppraisalMethod for Process Improvement. These authors have considerable experiencein helping their organizations appraise their respective levels of maturity inrelation to the CMMI. In this handy new book, they impart their advice on notonly achieving an accurate assessment, but also what next steps need to betaken for further process improvement. |
| cmmi data management maturity model: CMMI High Maturity Handbook Vishnuvarthanan Moorthy, 2015-06-23 CMMI High Maturity is something every software organization is interested in! Attaining Maturity Level 5 rating means world class processes in place in that organization. Though it’s everyone’s interest, there is less details available in the world on how to practically implement CMMI ML5 and how to interpret the High Maturity practices. This book is an attempt to decode the high maturity practices with clear sample cases for all the High maturity process areas, there by connecting the dots of Implementation. This book explains the practicality of implementation of CMMI ML5 and has given specific guidance in many cases. Obviously it is not the whole of CMMI or the whole of everything, however may be this is the only book which offers highest possible insight in CMMI High Maturity Implementation. What it offers: • Complete guide as an End to End CMMI High Maturity Implementation • Practical interpretation of CMMI Practices • Sample cases covering CMMI Dev and CMMI SVC Models v1.3 • Basic Statistical Concepts Required for Implementing High Maturity • Clarity in definition and difference between important terms • Connects the Entire High Maturity process areas • Implementer’s guide book offering relevant tips • Breaks the Myths behind High Maturity • High Maturity Understanding for Everyone What it is not: • Alternate to CMMI Model or describes all possible scenario of Implementing CMMI • Statistics Book Targeted Audience • CMMI Implementation Teams • CMMI Consultants • Quality Assurance Professionals • Software industry Professionals • Senior Management of Organizations, aspiring CMMI ML5 Journey • Anyone interested in CMMI or In Process Improvement Models. |
| cmmi data management maturity model: CMMI for Development Mary Beth Chrissis, Mike Konrad, Sandra Shrum, 2011-03-08 CMMI® for Development (CMMI-DEV) describes best practices for the development and maintenance of products and services across their lifecycle. By integrating essential bodies of knowledge, CMMI-DEV provides a single, comprehensive framework for organizations to assess their development and maintenance processes and improve performance. Already widely adopted throughout the world for disciplined, high-quality engineering, CMMI-DEV Version 1.3 now accommodates other modern approaches as well, including the use of Agile methods, Lean Six Sigma, and architecture-centric development. CMMI® for Development, Third Edition, is the definitive reference for CMMI-DEV Version 1.3. The authors have revised their tips, hints, and cross-references, which appear in the margins of the book, to help you better understand, apply, and find information about the content of each process area. The book includes new and updated perspectives on CMMI-DEV in which people influential in the model’s creation, development, and transition share brief but valuable insights. It also features four new case studies and five contributed essays with practical advice for adopting and using CMMI-DEV. This book is an essential resource–whether you are new to CMMI-DEV or are familiar with an earlier version–if you need to know about, evaluate, or put the latest version of the model into practice. The book is divided into three parts. Part One offers the broad view of CMMI-DEV, beginning with basic concepts of process improvement. It introduces the process areas, their components, and their relationships to each other. It describes effective paths to the adoption and use of CMMI-DEV for process improvement and benchmarking, all illuminated with fresh case studies and helpful essays. Part Two, the bulk of the book, details the generic goals and practices and the twenty-two process areas now comprising CMMI-DEV. The process areas are organized alphabetically by acronym for easy reference. Each process area includes goals, best practices, and examples. Part Three contains several useful resources, including CMMI-DEV-related references, acronym definitions, a glossary of terms, and an index. |
| cmmi data management maturity model: CMMI Implementation Guide , |
| cmmi data management maturity model: Data Governance Ismael Caballero, Mario Piattini, 2024-01-28 This book presents a set of models, methods, and techniques that allow the successful implementation of data governance (DG) in an organization and reports real experiences of data governance in different public and private sectors. To this end, this book is composed of two parts. Part I on “Data Governance Fundamentals” begins with an introduction to the concept of data governance that stresses that DG is not primarily focused on databases, clouds, or other technologies, but that the DG framework must be understood by business users, systems personnel, and the systems themselves alike. Next, chapter 2 addresses crucial topics for DG, such as the evolution of data management in organizations, data strategy and policies, and defensive and offensive approaches to data strategy. Chapter 3 then details the central role that human resources play in DG, analysing the key responsibilities of the different DG-related roles and boards, while chapter 4 discusses the most common barriers to DG in practice. Chapter 5 summarizes the paradigm shifts in DG from control to value creation. Subsequently chapter 6 explores the needs, characteristics and key functionalities of DG tools, before this part ends with a chapter on maturity models for data governance. Part II on “Data Governance Applied” consists of five chapters which review the situation of DG in different sectors and industries. Details about DG in the banking sector, public administration, insurance companies, healthcare and telecommunications each are presented in one chapter. The book is aimed at academics, researchers and practitioners (especially CIOs, Data Governors, or Data Stewards) involved in DG. It can also serve as a reference for courses on data governance in information systems. |
| cmmi data management maturity model: Data Model Scorecard Steve Hoberman, 2015-11-01 Data models are the main medium used to communicate data requirements from business to IT, and within IT from analysts, modelers, and architects, to database designers and developers. Therefore it’s essential to get the data model right. But how do you determine right? That’s where the Data Model Scorecard® comes in. The Data Model Scorecard is a data model quality scoring tool containing ten categories aimed at improving the quality of your organization’s data models. Many of my consulting assignments are dedicated to applying the Data Model Scorecard to my client’s data models – I will show you how to apply the Scorecard in this book. This book, written for people who build, use, or review data models, contains the Data Model Scorecard template and an explanation along with many examples of each of the ten Scorecard categories. There are three sections: In Section I, Data Modeling and the Need for Validation, receive a short data modeling primer in Chapter 1, understand why it is important to get the data model right in Chapter 2, and learn about the Data Model Scorecard in Chapter 3. In Section II, Data Model Scorecard Categories, we will explain each of the ten categories of the Data Model Scorecard. There are ten chapters in this section, each chapter dedicated to a specific Scorecard category: · Chapter 4: Correctness · Chapter 5: Completeness · Chapter 6: Scheme · Chapter 7: Structure · Chapter 8: Abstraction · Chapter 9: Standards · Chapter 10: Readability · Chapter 11: Definitions · Chapter 12: Consistency · Chapter 13: Data In Section III, Validating Data Models, we will prepare for the model review (Chapter 14), cover tips to help during the model review (Chapter 15), and then review a data model based upon an actual project (Chapter 16). |
| cmmi data management maturity model: CMMI Assessments Marilyn Bush, Donna Kastle Dunaway, 2005 Assessments remain at the cutting edge of process improvement, but very few practitioners what they are designed to do and how they work. |
| cmmi data management maturity model: Introduction to Software Process Improvement Gerard O'Regan, 2010-12-16 This textbook is a systematic guide to the steps in setting up a Capability Maturity Model Integration (CMMI) improvement initiative. Readers will learn the project management practices necessary to deliver high-quality software solutions to the customer on time and on budget. The text also highlights how software process improvement can achieve specific business goals to provide a tangible return on investment. Topics and features: supplies review questions, summaries and key topics for each chapter, as well as a glossary of acronyms; describes the CMMI model thoroughly, detailing the five maturity levels; provides a broad overview of software engineering; reviews the activities and teams required to set up a CMMI improvement initiative; examines in detail the implementation of CMMI in a typical organization at each of the maturity levels; investigates the various tools that support organizations in improving their software engineering maturity; discusses the SCAMPI appraisal methodology. |
| cmmi data management maturity model: Collaborative Enterprise Architecture Stefan Bente, Uwe Bombosch, Shailendra Langade, 2012-08-29 Why collaborative enterprise architecture? -- What is enterprise architecture -- What enterprise architects do: core activities of EA -- EA frameworks -- EA maturity models -- Foundations of collaborative EA -- Towards pragmatism: lean and agile EA -- Inviting to participation: eam 2.0 -- The next steps: taking collaborative EA forward. |
| cmmi data management maturity model: Data-Driven Decision-Making for Business Claus Grand Bang, 2024-08-22 Research shows that companies that employ data-driven decision-making are more productive, have a higher market value, and deliver higher returns for their shareholders. In this book, the reader will discover the history, theory, and practice of data-driven decision-making, learning how organizations and individual managers alike can utilize its methods to avoid cognitive biases and improve confidence in their decisions. It argues that value does not come from data, but from acting on data. Throughout the book, the reader will examine how to convert data to value through data-driven decision-making, as well as how to create a strong foundation for such decision-making within organizations. Covering topics such as strategy, culture, analysis, and ethics, the text uses a collection of diverse and up-to-date case studies to convey insights which can be developed into future action. Simultaneously, the text works to bridge the gap between data specialists and businesspeople. Clear learning outcomes and chapter summaries ensure that key points are highlighted, enabling lecturers to easily align the text to their curriculums. Data-Driven Decision-Making for Business provides important reading for undergraduate and postgraduate students of business and data analytics programs, as well as wider MBA classes. Chapters can also be used on a standalone basis, turning the book into a key reference work for students graduating into practitioners. The book is supported by online resources, including PowerPoint slides for each chapter. |
| cmmi data management maturity model: Organizational Project Management Maturity Model (OPM3) Project Management Institute, 2008 A second edition provides tools for organizations to measure their maturity against a comprehensive set of best practices, providing updated coverage of current PMI standards, guidelines for promoting smoother transitions and strategies for eliminating redundancy. |
| cmmi data management maturity model: The Virtual Team Maturity Model Ralf Friedrich, 2017-10-25 Ralf Friedrich developed an academically validated and process-oriented maturity model with emphasis on special needs of virtual teams. He provides criteria and indicators of performance for virtual teams and combines different approaches of maturity models into an overall framework to measure and develop virtual team performance.This book describes the development and validation of the Virtual Team Maturity Model (VTMM®) consisting of 11 processes for virtual team collaboration, defined by inputs, methods, outputs and Key Performance Indicators (KPIs) assigned to four maturity levels. The model supports an algorithm for calculating the maturity level of the team based on a set of questionnaires. |
| cmmi data management maturity model: Project Management Maturity Model J. Kent Crawford, 2006-07-24 Assisting organizations in improving their project management processes, the Project Management Maturity Model defines the industry standard for measuring project management maturity.Project Management Maturity Model, Second Edition provides a roadmap showing organizations how to move to higher levels of organizational behavior, improving |
| cmmi data management maturity model: CMMI Distilled Dennis M. Ahern, Aaron Clouse, Richard Turner, 2008 Updated for CMMI version 1.2, this edition provides concise and readable introduction to the model, as well as straightforward, no-nonsense information on integrated, continuous process improvement. |
| cmmi data management maturity model: Diverse Applications and Transferability of Maturity Models Katuu, Shadrack, 2018-10-19 Previously, professionals had to make judgment calls based on subjective criteria, including their own acumen, in their decision making. In order to combat this subjectivity, maturity models can be implemented to allow organizations a means of assessing everyday processes and to offer a path towards advancement using transparent objective criteria. Diverse Applications and Transferability of Maturity Models is a pivotal reference source that provides vital research on the application of maturity models in organizational development in a variety of work environments. While highlighting topics such as open government, archives and records management, enterprise content management, and digital economy, this publication explores methods to help organizations effectively implement plans in any given management system. This book is ideally designed for professionals and researchers seeking current research on a variety of social science and applied science fields including business studies, computer science, digital preservation, information governance, information science, information systems, public administration, records management, and project management. |
| cmmi data management maturity model: The Discipline of Data Jerald Savin, 2023-07-06 Pulling aside the curtain of ‘Big Data’ buzz, this book introduces C-suite and other non-technical senior leaders to the essentials of obtaining and maintaining accurate, reliable data, especially for decision-making purposes. Bad data begets bad decisions, and an understanding of data fundamentals — how data is generated, organized, stored, evaluated, and maintained — has never been more important when solving problems such as the pandemic-related supply chain crisis. This book addresses the data-related challenges that businesses face, answering questions such as: What are the characteristics of high-quality data? How do you get from bad data to good data? What procedures and practices ensure high-quality data? How do you know whether your data supports the decisions you need to make? This clear and valuable resource will appeal to C-suite executives and top-line managers across industries, as well as business analysts at all career stages and data analytics students. |
| cmmi data management maturity model: Data Lineage from a Business Perspective Irina Steenbeek, 2021-10 Data lineage has become a daily demand. However, data lineage remains an abstract/ unknown concept for many users. The implementation is complex and resource-consuming. Even if implemented, it is not used as expected. This book uncovers different aspects of data lineage for data management and business professionals. It provides the definition and metamodel of data lineage, demonstrates best practices in data lineage implementation, and discusses the key areas of data lineage usage. Several groups of professionals can use this book in different ways: Data management and business professionals can develop ideas about data lineage and its application areas. Professionals with a technical background may gain a better understanding of business needs and requirements for data lineage. Project management professionals can become familiar with the best practices of data lineage implementation. |
| cmmi data management maturity model: Using the Project Management Maturity Model Harold Kerzner, 2011-11-29 Updated for today's businesses-a proven model FOR assessment and ongoing improvement Using the Project Management Maturity Model, Second Edition is the updated edition of Harold Kerzner's renowned book covering his Project Management Maturity Model (PMMM). In this hands-on book, Kerzner offers a unique, industry-validated tool for helping companies of all sizes assess and improve their progress in integrating project management into every part of their organizations. Conveniently organized into two sections, this Second Edition begins with an examination of strategic planning principles and the ways they relate to project management. In the second section, PMMM is introduced with in-depth coverage of the five different levels of development for achieving maturity. Easily adaptable benchmarking instruments for measuring an organization's progress along the maturity curve make this a practical guide for any type of company. Complete with an associated Web site packed with both teaching and learning tools, Using the Project Management Maturity Model, Second Edition helps managers, engineers, project team members, business consultants, and others build a powerful foundation for company improvement and excellence. |
| cmmi data management maturity 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. |
| cmmi data management maturity model: Digital Libraries for Open Knowledge Eva Méndez, Fabio Crestani, Cristina Ribeiro, Gabriel David, João Correia Lopes, 2018-09-04 This book constitutes the proceedings of the 22nd International Conference on Theory and Practice of Digital Libraries, TPDL 2018, held in Porto, Portugal, in September 2018. The 51 full papers, 17 short papers, and 13 poster and tutorial papers presented in this volume were carefully reviewed and selected from 81 submissions. The general theme of TPDL 2018 was Digital Libraries for Open Knowledge. The papers present a wide range of the following topics: Metadata, Entity Disambiguation, Data Management, Scholarly Communication, Digital Humanities, User Interaction, Resources, Information Extraction, Information Retrieval, Recommendation. |
| cmmi data management maturity model: Implementing the Capability Maturity Model James R. Persse, 2001-08-27 Practical guidelines for an effective implementation of software development processes Designed to ensure effective software development processes, the Capability Maturity Model (CMM)--North America's leading standard for software development--requires companies to complete five steps, or levels, in the development process. But while it is widely adopted by Fortune 500 companies, many others get stuck at the initial planning stage. Focusing on Levels 2 and 3 of the CMM, this book helps readers to get over the hurdle of the two most problematic areas in this process--the project management and software development steps. It offers clear, step-by-step guidance on how to establish basic project management processes to track costs, schedules, and functionality; how to document, standardize, and integrate software processes; and how to improve software quality. |
| cmmi data management maturity model: The Data Management Cookbook Irina Steenbeek, 2018-03-16 A lot of companies realize that data is an invaluable asset and has to be managed accordingly. They would also like to get value from data. Everyone wants to be 'data-driven' these days. What lies beneath this idea, is the wish to make the decision-making process easier and more effective. It means delivering the required data of acceptable quality to the relevant decision makers when and where they need it. In short: a lot of companies have the necessity to manage their data properly. The main question is: how do you put this in practice? Knowing the potential of your data, and managing it correctly is the key to an effective and successful business. As a result of well-implemented data management, you will be able to reduce risks and costs, increase efficiency, ensure business continuity and successful growth. In this book, we invite you for a five-course dinner. During each course we will explain the steps of our 5-step programme which guarantees successful implementation of data management. |
| cmmi data management maturity model: Big Data Management Peter Ghavami, 2020-11-09 Data analytics is core to business and decision making. The rapid increase in data volume, velocity and variety offers both opportunities and challenges. While open source solutions to store big data, like Hadoop, offer platforms for exploring value and insight from big data, they were not originally developed with data security and governance in mind. Big Data Management discusses numerous policies, strategies and recipes for managing big data. It addresses data security, privacy, controls and life cycle management offering modern principles and open source architectures for successful governance of big data. The author has collected best practices from the world’s leading organizations that have successfully implemented big data platforms. The topics discussed cover the entire data management life cycle, data quality, data stewardship, regulatory considerations, data council, architectural and operational models are presented for successful management of big data. The book is a must-read for data scientists, data engineers and corporate leaders who are implementing big data platforms in their organizations. |
| cmmi data management maturity model: Software Process Improvement and Capability Determination Paul M. Clarke, Rory V. O'Connor, Terry Rout, Alec Dorling, 2016-05-11 This book constitutes the refereed proceedings of the 16th International Conference on Software Process Improvement and Capability Determination, SPICE 2016, held in Dublin, Ireland, in June 2016. The 28 full papers presented together with 5 short papers were carefully reviewed and selected from 52 submissions. The papers are organized in the following topical sections: SPI in regulated and safety critical domains; gamification and education issues in SPI; SPI in agile and small settings; SPI and assessment; SPI and project management concerns; empirical research case studies of SPI; knowledge and human communications issues in SPI. |
CMMI Institute - What is CMMI? - Capability Maturity Model …
The Capability Maturity Model Integration (CMMI) is a proven set of best practices that helps organizations understand their current level of capability and performance and offers a guide …
Capability Maturity Model Integration - Wikipedia
CMMI was developed by the CMMI project, which aimed to improve the usability of maturity models by integrating many different models into one framework. The project consisted of …
What is Capability Maturity Model Integration (CMMI)?
Jan 15, 2025 · The Capability Maturity Model Integration (CMMI) framework operates on three fundamental principles: process standardization, measurement-based improvement, and …
Background to Capability Maturity Model Integration (CMMI)
Jun 27, 2023 · CMMI-DEV is a model. It isn't a process, nor a prescription to be followed. Instead, CMMI-DEV provides a set of organizational behaviors that have proven to be of use in …
CMMI Institute - CMMI V2.0
Learn how CMMI V2.0 can take your organizational capability and performance to the next level. Request follow-up from a CMMI expert to learn how to get started.
Capability Maturity Model Integration (CMMI): An Introduction
Jan 13, 2025 · CMMI was developed by Carnegie Mellon University as part of the CMMI project. Its goal was to make maturity models—which measure the ability of organizations to have …
CMMI Performance Solutions - ISACA
CMMI is an outcome-based performance solution model that provides faster, better, and cheaper results for organizations. CMMI is the globally accepted standard that improves and enhances …
What is CMMI? A model for optimizing development processes
Jun 1, 2021 · The Capability Maturity Model Integration (CMMI) is a process and behavioral model that helps organizations streamline process improvement and encourage productive, …
Capability Maturity Model Integration (CMMI®) - KPMG
CMMI is a proven set of global best practices that drives business performance through building and benchmarking key capabilities. It can be used to guide process improvement across a …
CMMI Institute - Home
Browse through our collection of presentations, webinars, articles, case studies, and whitepapers to answer all your CMMI questions. Read the latest news, press releases and industry …
CMMI Institute - What is CMMI? - Capability Maturity Model …
The Capability Maturity Model Integration (CMMI) is a proven set of best practices that helps organizations understand their current level of capability and performance and offers a guide …
Capability Maturity Model Integration - Wikipedia
CMMI was developed by the CMMI project, which aimed to improve the usability of maturity models by integrating many different models into one framework. The project consisted of …
What is Capability Maturity Model Integration (CMMI)?
Jan 15, 2025 · The Capability Maturity Model Integration (CMMI) framework operates on three fundamental principles: process standardization, measurement-based improvement, and …
Background to Capability Maturity Model Integration (CMMI)
Jun 27, 2023 · CMMI-DEV is a model. It isn't a process, nor a prescription to be followed. Instead, CMMI-DEV provides a set of organizational behaviors that have proven to be of use in …
CMMI Institute - CMMI V2.0
Learn how CMMI V2.0 can take your organizational capability and performance to the next level. Request follow-up from a CMMI expert to learn how to get started.
Capability Maturity Model Integration (CMMI): An Introduction
Jan 13, 2025 · CMMI was developed by Carnegie Mellon University as part of the CMMI project. Its goal was to make maturity models—which measure the ability of organizations to have …
CMMI Performance Solutions - ISACA
CMMI is an outcome-based performance solution model that provides faster, better, and cheaper results for organizations. CMMI is the globally accepted standard that improves and enhances …
What is CMMI? A model for optimizing development processes
Jun 1, 2021 · The Capability Maturity Model Integration (CMMI) is a process and behavioral model that helps organizations streamline process improvement and encourage productive, …
Capability Maturity Model Integration (CMMI®) - KPMG
CMMI is a proven set of global best practices that drives business performance through building and benchmarking key capabilities. It can be used to guide process improvement across a …
CMMI Institute - Home
Browse through our collection of presentations, webinars, articles, case studies, and whitepapers to answer all your CMMI questions. Read the latest news, press releases and industry …
