By Gerhard Weikum, Srikanta Bedathur (auth.), Malu Castellanos, Umeshwar Dayal, Volker Markl (eds.)
ISBN-10: 3642229697
ISBN-13: 9783642229695
This ebook constitutes the completely refereed convention complaints of the 4th foreign Workshop on enterprise Intelligence for the Real-Time company, BIRTE 2010, held in Singapore, in September 2010, at the side of VLDB 2010, the overseas convention on Very huge information Bases.
The quantity comprises six study papers, that are rigorously reviewed and chosen out of 12 submissions, plus the 3 keynotes awarded on the workshop. the themes conceal all phases of the enterprise intelligence cycle, together with taking pictures of real-time info, dealing with of temproal or doubtful info, functionality matters, occasion administration, and the optimization of advanced ETL workflows.
Read Online or Download Enabling Real-Time Business Intelligence: 4th International Workshop, BIRTE 2010, Held at the 36th International Conference on Very Large Databases, VLDB 2010, Singapore, September 13, 2010, Revised Selected Papers PDF
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Additional info for Enabling Real-Time Business Intelligence: 4th International Workshop, BIRTE 2010, Held at the 36th International Conference on Very Large Databases, VLDB 2010, Singapore, September 13, 2010, Revised Selected Papers
Example text
Scale-out cluster and SAN were widely adapted by the industry due to the performance, scalability and high-availability it offered [9]. Many of the industry’s leading data warehouses ran on such configurations. com’s online recommendation system is fed by an industry standard Grid data warehouse [2]. 5 petabyte of user data. Its implementation uses a cluster of 96 servers [5]. Later in the decade an influx of TPC-H benchmark has been observed on massive scale-out clusters that supported large aggregate memory capacity delivering over a Million queries-per hour per 42-u rack.
The rapid decrease in the cost and size of data communications hardware and various sensor technologies offers to support a wealth of new businesses, loosely termed "sensor networks" [1][2]. It is common for customers to have 10’s, 100’s, or even 1000’s of data sources throughout their IT landscape. Yet these customers have a need for a holistic operational view across all of these data sources. New applications have been proposed in areas including intelligent highways, power grid management, intelligent battlefields, and remote product service and maintenance.
1. ” For example, up to 30,000 event correlations per second. 26 J. Navas • Cross-enterprise Automation - Automate the process of resolving new event requests to reduce the time-to-value for a new event question from the current industry standard of 5-6 person-weeks per question. • System Scaling - Throughput would be independent of data volume, quantity, and distribution pattern. For example, 2000 tier-one suppliers and 30,000 tiertwo suppliers. • Manage the data “in place” - But easily allow the flexible and ad hoc movement of data when necessary • Allow local control over data administration - But easily enable participation in broader data footprint of “integrated enterprise” • Layer on top of Existing Landscape - Within and across enterprises through standards already in place 3 Motivating Example in the Oil and Gas Industry Fig.
Enabling Real-Time Business Intelligence: 4th International Workshop, BIRTE 2010, Held at the 36th International Conference on Very Large Databases, VLDB 2010, Singapore, September 13, 2010, Revised Selected Papers by Gerhard Weikum, Srikanta Bedathur (auth.), Malu Castellanos, Umeshwar Dayal, Volker Markl (eds.)
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