標題: Titlebook: Enabling Real-Time Business Intelligence; Third International Malu Castellanos,Umeshwar Dayal,Renée J. Miller Conference proceedings 2010 [打印本頁] 作者: opioid 時間: 2025-3-21 18:06
書目名稱Enabling Real-Time Business Intelligence影響因子(影響力)
書目名稱Enabling Real-Time Business Intelligence影響因子(影響力)學科排名
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書目名稱Enabling Real-Time Business Intelligence網(wǎng)絡公開度學科排名
書目名稱Enabling Real-Time Business Intelligence被引頻次
書目名稱Enabling Real-Time Business Intelligence被引頻次學科排名
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書目名稱Enabling Real-Time Business Intelligence年度引用學科排名
書目名稱Enabling Real-Time Business Intelligence讀者反饋
書目名稱Enabling Real-Time Business Intelligence讀者反饋學科排名
作者: inquisitive 時間: 2025-3-21 21:42 作者: Spongy-Bone 時間: 2025-3-22 02:21 作者: 柳樹；枯黃 時間: 2025-3-22 06:06 作者: Highbrow 時間: 2025-3-22 11:41
Create and Test a Database and Table, as data warehousing, web log analysis, streams monitoring and social networks understanding necessitated the use of data cubes, grouping variables, windows and MapReduce. In this paper we review the associated set (ASSET) concept and discuss its applicability in both continuous and traditional data作者: sparse 時間: 2025-3-22 16:10 作者: sparse 時間: 2025-3-22 19:08
Correcting Tonality, Contrast, and Exposure,n and its appearance in the data warehouse. The most recent data is trapped in the operational sources where it is unavailable for analysis. For timely decision making, today’s business users asks for ever fresher data..Near real-time data warehousing addresses this challenge by shortening the data 作者: hegemony 時間: 2025-3-22 21:34
https://doi.org/10.1007/978-1-4302-2675-8the need and notion of real-time. The last few years have illuminated some key paradigms affecting data management. The arguments put forth to move away from traditional DBMS architectures have proven persuasive - and specialized architectural data stores are being adopted in the industry [1]. The c作者: 讓步 時間: 2025-3-23 02:27 作者: 漫不經(jīng)心 時間: 2025-3-23 09:34
https://doi.org/10.1007/978-1-4471-4585-1vestigate a stream-based join algorithm, called mesh join (MESHJOIN), and focus on a critical component in the algorithm, called the disk-buffer. In MESHJOIN the size of disk-buffer varies with a change in total memory budget and tuning is required to get the maximum service rate within limited avai作者: 場所 時間: 2025-3-23 10:37 作者: 著名 時間: 2025-3-23 15:36 作者: exquisite 時間: 2025-3-23 19:26 作者: harpsichord 時間: 2025-3-24 01:04 作者: 毛細血管 時間: 2025-3-24 02:56 作者: 易碎 時間: 2025-3-24 08:41
978-3-642-14558-2The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer-Verlag GmbH, DE作者: 永久 時間: 2025-3-24 14:41
Enabling Real-Time Business Intelligence978-3-642-14559-9Series ISSN 1865-1348 Series E-ISSN 1865-1356 作者: NOMAD 時間: 2025-3-24 17:53
VPipe: Virtual Pipelining for Scheduling of DAG Stream Query Plans,er, we propose a novel execution scheme for scheduling complex directed acyclic graph (DAG) query plans with meta-data enriched stream tuples. Our solution, called Virtual Pipelined Chain (or VPipe Chain for short), effectively extends the “Chain” pipelining scheduling approach to complex DAG query plans.作者: Altitude 時間: 2025-3-24 19:24
Conference proceedings 2010ecisions using integrated, trustworthy, and up-to-date data. Modern real-time enterprises need to act on events as they happen. They need new, easy-to-use intelligent solutions capable of analyzing heterogeneous real-time enterprise data to provide insight and actionable information at the right tim作者: EXUDE 時間: 2025-3-25 00:07 作者: 固執(zhí)點好 時間: 2025-3-25 04:28 作者: 愛社交 時間: 2025-3-25 09:45 作者: 顯而易見 時間: 2025-3-25 15:39
https://doi.org/10.1007/978-1-4471-4585-1n carried out between the optimum and reasonable default sizes for the disk-buffer. To avoid tuning, we propose a reasonable default value for the disk-buffer size with a small and acceptable performance loss. The experimental results validate our arguments.作者: 和音 時間: 2025-3-25 17:42
Practical Pathology Informaticsfferent views on different aggregation levels.Multi-dimensional queries exploiting hierarchically structured dimensions lead to complex star queries at a relational backend, which could hardly be handled by classical relational systems.作者: 伙伴 時間: 2025-3-25 20:53 作者: 現(xiàn)任者 時間: 2025-3-26 02:02
Near Real-Time Data Warehousing Using State-of-the-Art ETL Tools,reshment can no longer be performed in off-peak hours only. In particular, the source data may be changed concurrently to data warehouse refreshment. In this paper we show that anomalies may arise under these circumstances leading to an inconsistent state of the data warehouse and we propose approaches to avoid refreshment anomalies.作者: 沙發(fā) 時間: 2025-3-26 05:12 作者: 獸群 時間: 2025-3-26 11:17
Comparing Global Optimization and Default Settings of Stream-Based Joins,n carried out between the optimum and reasonable default sizes for the disk-buffer. To avoid tuning, we propose a reasonable default value for the disk-buffer size with a small and acceptable performance loss. The experimental results validate our arguments.作者: neuron 時間: 2025-3-26 16:20
,Merging OLTP and OLAP – Back to the Future,fferent views on different aggregation levels.Multi-dimensional queries exploiting hierarchically structured dimensions lead to complex star queries at a relational backend, which could hardly be handled by classical relational systems.作者: 偽書 時間: 2025-3-26 19:37 作者: 啤酒 時間: 2025-3-27 00:47
ASSET Queries: A Set-Oriented and Column-Wise Approach to Modern OLAP,rrelated, resembling a spreadsheet document. We review systems implementing ASSET queries both in continuous and persistent contexts and argue for associated sets’ analytical abilities and optimization opportunities.作者: Filibuster 時間: 2025-3-27 03:41 作者: 低位的人或事 時間: 2025-3-27 07:25 作者: Maximizer 時間: 2025-3-27 13:00 作者: 說不出 時間: 2025-3-27 14:56 作者: instate 時間: 2025-3-27 17:52 作者: CRATE 時間: 2025-3-27 23:48 作者: Bph773 時間: 2025-3-28 04:57
https://doi.org/10.1007/978-1-4842-4346-6e above operations via imprecise data models. CRFs provide a sound probability distribution over extractions but are not easy to represent and query in a relational framework. We present methods of approximating this distribution to query-friendly row and column uncertainty models. Finally, we prese作者: 審問 時間: 2025-3-28 08:56
Bo Feng,Xiaohui Mi,Xun Bi,Zhonglin Murespect to given costs for document extraction we propose two novel join-operations: The multi-way CJ-operator joins records from multiple relationships extracted from a single document. The two-way join-operator DJ ensures data density by removing incomplete records from results. In a preliminary c作者: 用肘 時間: 2025-3-28 11:14
https://doi.org/10.1007/978-1-4302-2675-8ems. The enterprise is overflowing with data streams that require instantaneous processing and integration, to deliver faster visibility and invoke conjoined actions for RT decision making, resulting in deployment of advanced BI applications as can be seen by stream processing over RT feeds from ope作者: Liberate 時間: 2025-3-28 17:08
Conference proceedings 2010ata warehousing, and event and business process modeling. The series of BIRTE workshops aims to provide a forum to discuss and advance the foundational science and engineering required to enable real-time business intel- gence and the novel applications and solutions that build on these foundational作者: 酷熱 時間: 2025-3-28 20:15
Queries over Unstructured Data: Probabilistic Methods to the Rescue,challenge of modern business intelligence applications is analyzing and querying data seamlessly across structured and unstructured sources. This requires the development of automated techniques for extracting structured records from text sources and resolving entity mentions in data from various so作者: 喊叫 時間: 2025-3-29 02:24
Federated Stream Processing Support for Real-Time Business Intelligence Applications,uilds on and extends the SAP MaxDB relational database system in order to provide a federator over multiple underlying stream processing engines and databases. We show preliminary results on usefulness and performance of the MaxStream architecture on the SAP Sales and Distribution Benchmark.作者: GONG 時間: 2025-3-29 06:34
VPipe: Virtual Pipelining for Scheduling of DAG Stream Query Plans,ystem such as CHAOS [1] (Continuous, Heterogeneous Analytic Over Streams), handling of complex query plans with resource constraints is challenging. While several scheduling strategies exist for stream processing, efficient scheduling of complex DAG query plans is still largely unsolved. In this pap作者: 墊子 時間: 2025-3-29 10:49
,Ad-Hoc Queries over Document Collections – A Case Study,0.000’s of documents from an ad-hoc web search result. Neither conventional search engines nor conventional Business Intelligence and ETL tools address this problem, which lies at the intersection of their capabilities. “Google Squared” or our system GOOLAP.info, are examples of these kinds of syste作者: anchor 時間: 2025-3-29 15:07 作者: 半球 時間: 2025-3-29 17:49 作者: 同位素 時間: 2025-3-29 22:57
Near Real-Time Data Warehousing Using State-of-the-Art ETL Tools,n and its appearance in the data warehouse. The most recent data is trapped in the operational sources where it is unavailable for analysis. For timely decision making, today’s business users asks for ever fresher data..Near real-time data warehousing addresses this challenge by shortening the data 作者: 弄臟 時間: 2025-3-30 03:50
Addressing BI Transactional Flows in the Real-Time Enterprise Using GoldenGate TDM,the need and notion of real-time. The last few years have illuminated some key paradigms affecting data management. The arguments put forth to move away from traditional DBMS architectures have proven persuasive - and specialized architectural data stores are being adopted in the industry [1]. The c作者: 幻想 時間: 2025-3-30 05:57
