Knowledge Management In The Development Of Data Intensive Systems

Data-intensive systems are software applications that process and generate Big Data. Data-intensive systems support the use of large amounts of data strategically and efficiently to provide intelligence. For example, examining industrial sensor data or business process data can enhance production, guide proactive improvements of development processes, or optimize supply chain systems. Designing data-intensive software systems is difficult because distribution of knowledge across stakeholders creates a symmetry of ignorance, because a shared vision of the future requires the development of new knowledge that extends and synthesizes existing knowledge. Knowledge Management in the Development of Data-Intensive Systems addresses new challenges arising from knowledge management in the development of data-intensive software systems. These challenges concern requirements, architectural design, detailed design, implementation and maintenance. The book covers the current state and future directions of knowledge management in development of data-intensive software systems. The book features both academic and industrial contributions which discuss the role software engineering can play for addressing challenges that confront developing, maintaining and evolving systems;data-intensive software systems of cloud and mobile services; and the scalability requirements they imply. The book features software engineering approaches that can efficiently deal with data-intensive systems as well as applications and use cases benefiting from data-intensive systems. Providing a comprehensive reference on the notion of data-intensive systems from a technical and non-technical perspective, the book focuses uniquely on software engineering and knowledge management in the design and maintenance of data-intensive systems. The book covers constructing, deploying, and maintaining high quality software products and software engineering in and for dynamic and flexible environments. This book provides a holistic guide for those who need to understand the impact of variability on all aspects of the software life cycle. It leverages practical experience and evidence to look ahead at the challenges faced by organizations in a fast-moving world with increasingly fast-changing customer requirements and expectations.

This volume presents a methodology for defining, measuring and improving data quality. It lays out an economic framework for understanding the value of data quality, then outlines data quality rules and domain- and mapping-based approaches to consolidating enterprise knowledge.

This book serves as a complete introduction to the subject of Knowledge Management (KM), and incorporates technical as well as social aspects, concepts as well as practical examples, and traditional KM approaches as well as emerging topics. Knowledge Management: Systems and Processes enhances the conventional exposition of KM with an in-depth discussion of the technologies used to facilitate the management of knowledge in large and small organizations. This includes a complete description of the theory and applications of the various techniques and technologies currently in use to manage organizational knowledge. The discussion of technology is at a level appropriate for the typical business administration graduate student or corporate manager. Special features: * Includes case studies of actual implementations of KM systems, including details such as system architecture * Contains numerous vignettes describing practical applications of KM initiatives at leading firms and governmental organizations * Provides a balanced view of knowledge management, while incorporating benefits and controversial issues, and both technology and social aspects * Extremely current, making extensive use of latest developments in, and examples from, the field of KM * Written by two proficient and recognized researchers in the field of KM.

Information and knowledge have fundamentally transformed the way businesses and social institutions work. Knowledge management promises concepts and instruments that help organizations to create an environment supportive of knowledge creation, sharing and application. Information and communication technologies (ICT) are often regarded as the enabler for knowledge management initiatives. The book presents an almost encyclopedic treatise of the facets, concepts and theories that have influenced knowledge management and the state of practice concerning strategy, organization, systems and economics. The second edition updates the material to cover the most recent developments in ICT-supported knowledge management. The book particularly provides a more in-depth coverage of its theoretical foundation including a new account of knowledge work, discusses the potentials and challenges of process-oriented knowledge management, adds a new chapter on modelling that plays an important role in knowledge management initiatives and contrasts architectures for centralized and distributed or peer-to-peer knowledge management systems.

Knowledge: In the realm of knowledge management, information plus wisdom equals knowledge. Organizations have found that the knowledge they contain can be one of their most important competitive weapons Definition: Knowledge management: The ability of an organization to manage, store, value, and distribute knowledge. Some organizations have created the position of Chief Knowledge Manager (CKM) to handle knowledge management responsibilities Many organizations fail to effectively manage and use the most important competitive edge they possess - their knowledge and "intellectual capital." This book covers the entire growing field of knowledge management, with particular emphasis on knowledge-based systems and their use in preserving knowledge in an organization, and integrating it across departments and disciplines. This hands-on guide shows how businesses and other organizations can re-engineer their processes using an applied knowledge-based approach. Each chapter introduces a different aspect of the field and demonstrates its application in actual case studies. Examples from industry, education, and government show the wide application of this exciting new field of study. The book also covers promising trends such as learning organizations, intelligent organizations, and enterprise management.

This book has been written by studying the knowledge management implementation at POWERGRID India, one of the largest power distribution companies in the world. The patterns which have led to models, both hypothesized and data-enabled, have been provided. The book suggests ways and means to follow for knowledge management implementation, especially for organizations with multiple business verticals to follow. The book underlines that knowledge is both an entity and organizational asset which can be managed. A holistic view of knowledge management implementation has been provided. It also emphasizes the phenomenological importance of human resource parameters as compared to that of technological parameters. Various hypotheses have been tested to validate the significant models hypothesized. This work will prove useful to corporations, researchers, and independent professionals working to study or implement knowledge management paradigms.

Data is at the center of many challenges in system design today. Difficult issues need to be figured out, such as scalability, consistency, reliability, efficiency, and maintainability. In addition, we have an overwhelming variety of tools, including relational databases, NoSQL datastores, stream or batch processors, and message brokers. What are the right choices for your application? How do you make sense of all these buzzwords? In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Peer under the hood of the systems you already use, and learn how to use and operate them more effectively Make informed decisions by identifying the strengths and weaknesses of different tools Navigate the trade-offs around consistency, scalability, fault tolerance, and complexity Understand the distributed systems research upon which modern databases are built Peek behind the scenes of major online services, and learn from their architectures

Recent research shows that collaboration and social networking foster knowledge sharing and innovation by sparking new connections, ideas, and practices. Yet these informal networks are often misunderstood and poorly managed. Building on the groundbreaking, bestselling first edition, Knowledge Management Handbook: Collaboration and Social Networkin