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Model management and analytics for large scale systems /

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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Otros Autores: Tekinerdogan, Bedir, 1970- (Editor ), Babur, Önder (Editor ), Cleophas, Loek (Editor ), Brand, Mark van den (Editor ), Akşit, Mehmet (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: London, United Kingdom : Academic Press, an imprint of Elsevier, [2020]
Temas:
Acceso en línea:Texto completo (Requiere registro previo con correo institucional)

MARC

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245 0 0 |a Model management and analytics for large scale systems /  |c edited by Bedir Tekinerdogan, Önder Babur, Loek Cleophas, Mark van den Brand, Mehmet Aksit. 
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500 |a Includes index. 
588 0 |a Online resource; title from PDF title page (ScienceDirect, viewed October 2, 2019). 
504 |a Includes bibliographical references and index. 
520 |a 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. 
590 |a O'Reilly  |b O'Reilly Online Learning: Academic/Public Library Edition 
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700 1 |a Tekinerdogan, Bedir,  |d 1970-  |e editor. 
700 1 |a Babur, Önder,  |e editor. 
700 1 |a Cleophas, Loek,  |e editor. 
700 1 |a Brand, Mark van den,  |e editor. 
700 1 |a Akşit, Mehmet,  |e editor. 
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