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...
| Main Authors: | , , , , , |
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| Format: | software, multimedia |
| Language: | eng |
| Published: |
London : Academic Press an imprint of Elsevier,
2019
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| Subjects: | |
| Online Access: | https://www.sciencedirect.com/science/book/9780128166499 |
| _version_ | 1796765043215302656 |
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| author | Tekinerdogan, Bedir, editor 648550 Babur, Önder, editor 648551 Cleophas, Loek, editor 648552 Van Den Brand, Mark, editor 648553 Akşit, Mehmet, editor 309203 ScienceDirect (Online service) 7722 |
| author_facet | Tekinerdogan, Bedir, editor 648550 Babur, Önder, editor 648551 Cleophas, Loek, editor 648552 Van Den Brand, Mark, editor 648553 Akşit, Mehmet, editor 309203 ScienceDirect (Online service) 7722 |
| author_sort | Tekinerdogan, Bedir, editor 648550 |
| collection | OCEAN |
| description | 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 |
| first_indexed | 2024-03-05T17:18:35Z |
| format | software, multimedia |
| id | KOHA-OAI-TEST:605900 |
| institution | Universiti Teknologi Malaysia - OCEAN |
| language | eng |
| last_indexed | 2024-03-05T17:18:35Z |
| publishDate | 2019 |
| publisher | London : Academic Press an imprint of Elsevier, |
| record_format | dspace |
| spelling | KOHA-OAI-TEST:6059002023-11-11T12:49:51ZModel Management and Analytics for Large Scale Systems / Tekinerdogan, Bedir, editor 648550 Babur, Önder, editor 648551 Cleophas, Loek, editor 648552 Van Den Brand, Mark, editor 648553 Akşit, Mehmet, editor 309203 ScienceDirect (Online service) 7722 software, multimedia Electronic books 631902 London : Academic Press an imprint of Elsevier,©20202019engModel 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. directionsPart 1. Concepts and challenges -- Part 2. Methods and tools -- Part 3. Industrial applications 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. directionsLarge scale systemshttps://www.sciencedirect.com/science/book/9780128166499URN:ISBN:9780128166499Remote access restricted to users with a valid UTM ID via VPN. |
| spellingShingle | Large scale systems Tekinerdogan, Bedir, editor 648550 Babur, Önder, editor 648551 Cleophas, Loek, editor 648552 Van Den Brand, Mark, editor 648553 Akşit, Mehmet, editor 309203 ScienceDirect (Online service) 7722 Model Management and Analytics for Large Scale Systems / |
| title | Model Management and Analytics for Large Scale Systems / |
| title_full | Model Management and Analytics for Large Scale Systems / |
| title_fullStr | Model Management and Analytics for Large Scale Systems / |
| title_full_unstemmed | Model Management and Analytics for Large Scale Systems / |
| title_short | Model Management and Analytics for Large Scale Systems / |
| title_sort | model management and analytics for large scale systems |
| topic | Large scale systems |
| url | https://www.sciencedirect.com/science/book/9780128166499 |
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