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Titlebook: Real-Time Business Intelligence and Analytics; International Worksh Malu Castellanos,Panos K. Chrysanthis,Konstantinos Conference proceedin

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發(fā)表于 2025-3-21 16:25:24 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書(shū)目名稱Real-Time Business Intelligence and Analytics
副標(biāo)題International Worksh
編輯Malu Castellanos,Panos K. Chrysanthis,Konstantinos
視頻videohttp://file.papertrans.cn/823/822251/822251.mp4
叢書(shū)名稱Lecture Notes in Business Information Processing
圖書(shū)封面Titlebook: Real-Time Business Intelligence and Analytics; International Worksh Malu Castellanos,Panos K. Chrysanthis,Konstantinos Conference proceedin
描述.This book constitutes the thoroughly refereed conference proceedings of the BIRTE workshops listed below, which were held in in conjunction with VLDB, the International Conference on Very Large Data Bases:...9th International Workshop on BusinessIntelligence for the Real-Time Enterprise, BIRTE 2015, held in KohalaCoast, Hawaii, in August 2015,?..10th International Workshop on Enabling Real-TimeBusiness Intelligence, BIRTE 2016, held in New Delhi, India, in September2016,.11th International Workshop on Real-Time BusinessIntelligence and Analytics, BIRTE 2017, held in Munich, Germany, in August2017.. .The BIRTE workshop series provides a forum for the discussion and advancement of the science and engineering enabling real-time business intelligence and the novel applications that build on these foundational techniques..The book includes five selected papers from BIRTE 2015; five selected papersfrom BIRTE 2016; and three selected papers from BIRTE 2017.?.
出版日期Conference proceedings 2019
關(guān)鍵詞OLAP; big data; business intelligence; data analytics; data warehouses; online analytical processing; stre
版次1
doihttps://doi.org/10.1007/978-3-030-24124-7
isbn_softcover978-3-030-24123-0
isbn_ebook978-3-030-24124-7Series ISSN 1865-1348 Series E-ISSN 1865-1356
issn_series 1865-1348
copyrightSpringer Nature Switzerland AG 2019
The information of publication is updating

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Processing of Aggregate Continuous Queries in a Distributed Environmentn this paper, we study the problem of generating high quality execution plans of . in . deployed on multi-node (multi-core and multi-processor) distributed environments. Towards this goal, we classify optimizers based on how they partition the workload among computing nodes and on their usage of the
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Past and Future Steps for Adaptive Storage Data Systems: From Shallow to Deep Adaptivityprimarily for the case of adaptive indexing to automatically create the right indexes at the right granularity. More recently work on adaptive loading and adaptive data layouts brought even more flexibility. We survey this work and describe the need for even deeper adaptivity that goes beyond adjust
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