Model Management And Analytics For Large Scale Systems
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Model Management And Analytics For Large Scale Systems
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Author : Bedir Tekinerdogan
language : en
Publisher: Academic Press
Release Date : 2019-09-14
Model Management And Analytics For Large Scale Systems written by Bedir Tekinerdogan and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-14 with Computers categories.
Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management. - Identifies key problems and offers solution approaches and tools that have been developed or are necessary for model management and analytics - Explores basic theory and background, current research topics, related challenges and the research directions for model management and analytics - Provides a complete overview of model management and analytics frameworks, the different types of analytics (descriptive, diagnostics, predictive and prescriptive), the required modelling and method steps, and important future directions
Business Modeling And Software Design
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Author : Boris Shishkov
language : en
Publisher: Springer Nature
Release Date : 2020-07-06
Business Modeling And Software Design written by Boris Shishkov and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-06 with Computers categories.
This book constitutes the refereed proceedings of the 10th International Symposium on Business Modeling and Software Design, BMSD 2020, which took place in Berlin, Germany, in July 2020. BMSD is a leading international forum that brings together researchers and practitioners interested in business modeling and its relation to software design. Particular areas of interest are: Business Processes and Enterprise Engineering; Business Models and Requirements; Business Models and Services; Business Models and Software; Information Systems Architectures and Paradigms; Data Aspects in Business Modeling and Software Development; Blockchain-Based Business Models and Information Systems; IoT and Implications for Enterprise Information Systems. The theme of BMSD 2020 was: Towards Knowledge-Driven Enterprise Information Systems.
Knowledge Management In The Development Of Data Intensive Systems
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Author : Ivan Mistrik
language : en
Publisher: CRC Press
Release Date : 2021-06-15
Knowledge Management In The Development Of Data Intensive Systems written by Ivan Mistrik and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-15 with Computers categories.
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.
New Trends In Database And Information Systems
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Author : Silvia Chiusano
language : en
Publisher: Springer Nature
Release Date : 2022-08-29
New Trends In Database And Information Systems written by Silvia Chiusano and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-08-29 with Computers categories.
This book constitutes the proceedings of the 26th European Conference on Advances in Databases and Information Systems, ADBIS 2022, held in Turin, Italy, in September 2022. The 29 short papers presented were carefully reviewed and selected from 90 submissions. The selected short papers are organized in the following sections: data understanding, modeling and visualization; fairness in data processing; data management pipeline, information and process retrieval; data access optimization; data pre-processing and cleaning; data science and machine learning. Further, papers from the following workshops and satellite events are provided in the volume: DOING: 3rd Workshop on Intelligent Data – From Data to Knowledge; K-GALS: 1st Workshop on Knowledge Graphs Analysis on a Large Scale; MADEISD: 4th Workshop on Modern Approaches in Data Engineering and Information System Design; MegaData: 2nd Workshop on Advanced Data Systems Management, Engineering, and Analytics; SWODCH: 2nd Workshop on Semantic Web and Ontology Design for Cultural Heritage; Doctoral Consortium.
Consistent View Based Management Of Variability In Space And Time
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Author : Ananieva, Sofia
language : en
Publisher: KIT Scientific Publishing
Release Date : 2022-12-06
Consistent View Based Management Of Variability In Space And Time written by Ananieva, Sofia and has been published by KIT Scientific Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-06 with Computers categories.
Developing variable systems faces many challenges. Dependencies between interrelated artifacts within a product variant, such as code or diagrams, across product variants and across their revisions quickly lead to inconsistencies during evolution. This work provides a unification of common concepts and operations for variability management, identifies variability-related inconsistencies and presents an approach for view-based consistency preservation of variable systems.
Advanced Informatics For Computing Research
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Author : Ashish Kumar Luhach
language : en
Publisher: Springer Nature
Release Date : 2021-06-19
Advanced Informatics For Computing Research written by Ashish Kumar Luhach and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-19 with Computers categories.
This two-volume set (CCIS 1393 and CCIS 1394) constitutes selected and revised papers of the 4th International Conference on Advanced Informatics for Computing Research, ICAICR 2020, held in Gurugram, India, in December 2020. The 34 revised full papers and 51 short papers presented were carefully reviewed and selected from 306 submissions. The papers are organized in topical sections on computing methodologies; hardware; networks; security and privacy.
Large Scale And Big Data
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Author : Sherif Sakr
language : en
Publisher: CRC Press
Release Date : 2014-06-25
Large Scale And Big Data written by Sherif Sakr and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-06-25 with Computers categories.
Large Scale and Big Data: Processing and Management provides readers with a central source of reference on the data management techniques currently available for large-scale data processing. Presenting chapters written by leading researchers, academics, and practitioners, it addresses the fundamental challenges associated with Big Data processing t
Stochastic Modeling And Analytics In Healthcare Delivery Systems
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Author : Jingshan Li
language : en
Publisher: World Scientific
Release Date : 2017-09-22
Stochastic Modeling And Analytics In Healthcare Delivery Systems written by Jingshan Li and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-22 with Medical categories.
In recent years, there has been an increased interest in the field of healthcare delivery systems. Scientists and practitioners are constantly searching for ways to improve the safety, quality and efficiency of these systems in order to achieve better patient outcome.This book focuses on the research and best practices in healthcare engineering and technology assessment. With contributions from researchers in the fields of healthcare system stochastic modeling, simulation, optimization and management, this is a valuable read.
Spatiotemporal Data Analytics And Modeling
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Author : John A
language : en
Publisher: Springer Nature
Release Date : 2024-04-15
Spatiotemporal Data Analytics And Modeling written by John A and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-15 with Computers categories.
With the growing advances in technology and transformation to digital services, the world is becoming more connected and more complex. Huge heterogeneous data are generated at rapid speed from various types of sensors. Augmented with artificial intelligence and machine learning and internet of things, latent relations, and new insights can be captured helping in optimizing plans and resource utilization, improving infrastructure, and enhancing quality of services. A “spatial data management system” is a way to take care of data that has something to do with space. This could include data such as maps, satellite images, and GPS data. A temporal data management system is a system designed to manage data that has a temporal component. This could include data such as weather data, financial data, and social media data. Some advanced techniques used in spatial and temporal data management systems include geospatial indexing for efficient querying and retrieval of location-based data, time-series analysis for understanding and predicting temporal patterns in datasets like weather or financial trends, machine learning algorithms for uncovering hidden patterns and correlations in large and complex datasets, and integration with Internet of Things (IoT) technologies for real-time data collection and analysis. These techniques, augmented with artificial intelligence, enable the extraction of latent relations and insights, thereby optimizing plans, improving infrastructure, and enhancing the quality of services. This book provides essential technical knowledge, best practices, and case studies on the state-of-the-art techniques of artificial intelligence and machine learning for spatiotemporal data analysis and modeling. The book is composed of several chapters written by experts in their fields and focusing on several applications including recommendation systems, big data analytics, supply chains and e-commerce, energy consumption and demand forecasting,and traffic and environmental monitoring. It can be used as academic reference at graduate level or by professionals in science and engineering related fields such as data science and engineering, big data analytics and mining, artificial intelligence, machine learning and deep learning, cloud computing, and internet of things.
Run Time Models For Self Managing Systems And Applications
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Author : Danilo Ardagna
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-11-15
Run Time Models For Self Managing Systems And Applications written by Danilo Ardagna and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-15 with Computers categories.
The complexity of Information Technology (IT) systems has been steadily incre- ing in the past decades. In October 2001, IBM released the “Autonomic Computing Manifesto” observing that current applications have reached the size of millions of lines of code, while physical infrastructures include thousands of heterogeneous servers requiring skilled IT professionals to install, con?gure, tune, and maintain. System complexity has been recognized as the main obstacle to the further advan- ment of IT technology. The basic idea of Autonomic Computing is to develop IT systems that are able to manage themselves, as the human autonomic nervous system governs basic body functions such as heart rate or body temperature, thus freeing the conscious brain— IT administrators—from the burden of dealing with low-level vital functions. Autonomic Computing systems can be implemented by introducing autonomic controllers which continuously monitor, analyze, plan, and execute (the famous MAPE cycle) recon?guration actions on the system components. Monitoring acti- ties are deployed to measure the workload and performance metrics of each running component so as to identify system faults. The goal of the analysis activities is to determine the status of components from the monitoring data, and to forecast - ture conditions based on historical observations. Finally, plan and execute activities aim at deciding and actuating the next system con?guration, for example, deciding whether to accept or reject new requests, determining the best application to servers assignment, in order to the achieve the self-optimization goals.