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Titlebook: Enabling Real-Time Business Intelligence; 4th International Wo Malu Castellanos,Umeshwar Dayal,Volker Markl Conference proceedings 2011 Spr

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One Size Fits all, Again! The Architecture of the Hybrid OLTP&OLAP Database Management System HyPer separation of transaction processing on the OLTP database and BI query processing on the . that is only periodically refreshed violates this goal. We propose to enhance the transactional database with highly effective query processing capabilities. We contrast different architectures proposed for a
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Building Enterprise Class Real-Time Energy Efficient Decision Support Systems, while generating Terabytes of data per day [2]. The ability to convert this data into meaningful business information in a timely, cost effective manner is critical to their competitiveness. For many, it is no longer acceptable to move operational data into specialized analytical tools because of t
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Data Quality Is Context Dependent,ts for the assessment and usage of a data source at hand are modeled as collections of external databases, that can be materialized or virtual, and mappings within the collections and with the data source at hand. In this way, the context becomes “the complement” of the data source wrt a data integr
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An Efficient Heuristic for Logical Optimization of ETL Workflows, observe that only some of the dependencies in an ETL flow are . while others are basically represents the flow of data. For the linear flows, we exploit the underlying dependency graph and develop a greedy heuristic technique to determine a reordering that significantly improves the quality of the
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Augmenting Tables by Self-supervised Web Search,ngines have the capacity to aggregate the wealth of information hidden in Web pages that could be used to return these missing values. Therefore exploiting this information with structured queries, such as join queries, is an often requested, but still unsolved requirement of many Web users..A major
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Handling of Uncertainty and Temporal Indeterminacy for What-if Analysis,y increased the value of decision support. However, the highly relevant aspect of representing and processing uncertain and temporally indeterminate data is often ignored in this context. Although the management of uncertainty has been researched intensely in the last decade, its role in decision su
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