Titlebook: Enabling Real-Time Business Intelligence; Third International Malu Castellanos,Umeshwar Dayal,Renée J. Miller Conference proceedings 2010

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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

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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

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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.

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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

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,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

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同位素

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

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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

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