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Enabling Real-Time Business Intelligence Third International Workshop, BIRTE 2009, Held at the 35th International Conference on Very Large Databases, VLDB 2009, Lyon, France, August 24, 2009, Revised Selected Papers

:	Malu Castellanos, Umeshwar Dayal, Renée J. Miller
:	Enabling Real-Time Business Intelligence Third International Workshop, BIRTE 2009, Held at the 35th International Conference on Very Large Databases, VLDB 2009, Lyon, France, August 24, 2009, Revised Selected Papers
:	Springer-Verlag
:	9783642145599
:	1
:	CHF 43.90
:

:	Sonstiges
:	English

:	181
:	DRM
:	PC/MAC/eReader/Tablet
:	PDF

This book constitutes the thoroughly refereed post-conference proceedings of the Third International Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2009, held in Lyon, France, in August 2009, in conjunction with VLDB 2009, the International Conference on Very Large Data Bases. The volume contains the carefully reviewed selected papers from the workshop, including one of the two keynotes, the six research, two industrial, and one experimental paper, and also the basic statements from the panel discussion on"Merging OLTP and OLAP". The topical focus is on models and concepts, architectures, case-studies, and applications of technologies for real-time enterprise business intelligence.

	Preface	5
	Organization	6
	Table of Contents	7
	Queries over Unstructured Data: Probabilistic Methods to the Rescue (Keynote)	8
	Unstructured Data in Enterprises	8
	Probabilistic Models for Information Extraction	10
	Representing Noisy Extractions as Imprecise Databases	11
	Multi-attribute Extractions	13
	Imprecise Data Models for Representing Uncertainty of De-duplication	15
	Probability of Two Records Being Duplicates	15
	Probability over Entity Groupings	15
	Queries over Imprecise Duplicates	16
	Concluding Remarks	18
	References	19
	Federated Stream Processing Support for Real-Time Business Intelligence Applications	21
	Introduction	21
	Related Work	22
	The MaxStream Federated Stream Processing System	24
	Architecture	26
	Two Key Building Blocks	28
	Hybrid Queries: Using Persistence with Streams	30
	Using MaxStream in Real-Time BI Scenarios	32
	Reducing Latency in Event-Driven Business Intelligence	32
	Persistent Events in Supply-Chain Monitoring	33
	Other Real-Time BI Applications	34
	Feasibility Study	34
	Conclusions and Future Directions	36
	References	37
	VPipe: Virtual Pipelining for Scheduling of DAG Stream Query Plans	39
	Introduction	39
	Preliminaries	42
	Review of the Chain Scheduling	42
	Problem Definition	43
	The VPipe Execution Scheme	44
	Change of Operator Logic	45
	Discussion	47
	Stochastic Analysis of Chain	47
	System Model Basis	48
	Case 1: System Analysis for SOS Synchronization	48
	Case 2: System Analysis for IDS Synchronization	50
	Performance Study	53
	Experiment 1: Response Time Comparison	53
	Experiment 2: Broken Pipeline Probability	54
	Related Work	54
	Conclusion	55
	References	55
	Ad-Hoc Queries over Document Collections – A Case Study	57
	Introduction	57
	Query Planning and Query Plan Execution	59
	Understanding “Human-Powered” Query Execution Strategies	59
	Elementary Plan Operators	60
	The Coverage-Join (CJ) and Density-Join (DJ) Operator	64
	Example Query and Example Plans	64
	Plan Enumeration	65
	Case Study	66
	Heuristics for Plan Selection	66
	Results and Discussion	67
	Related Work	69
	Summary and Future Work	70
	References	71
	Appendix: Implementing the KEYWORD-Operator	72
	ASSET Queries: A Set-Oriented and Column-Wise Approach to Modern OLAP	73
	Introduction	73
	Grouping Analysis: A Retrospective	74
	Group by	75
	Cubes	75
	Grouping Variables and the MD-Join	76
	Windows	76
	MapReduce	77
	Associated Sets (ASSET) Queries	77
	Definitions	77
	SQL Syntax	78
	DataMingler: A Spreadsheet-Like GUI	79
	ASSET Queries and Data Streams (COSTES)	80
	Financial Application Motivating Examples	81
	COSTES: Continuous Spreadsheet-Like Computations	83
	ASSET Queries and Persistent Data Sources (ASSET QE)	84
	Social Networks: A Motivating Example	84
	ASSET Query Engine (QE)	86
	Conclusions and Future Work	88
	References	89
	Evaluation of Load Scheduling Strategies for Real-Time Data Warehouse Environments	91
	Introduction	91
	System Model and Problem Statement	93
	System Architecture	93
	Workload Model	94
	Scheduling Performance Objective	95
	Problem Statement	96
	Scheduling Policies	97
	Scheduling Algorithms for Push-Based Update Propagation	97
	Evaluation and Discussion	98
	Simulation Framework	98
	Effect of the Data Production Process Length	99
	Comparison of Local and Global Scheduling	100
	Effects of Stage-Concurrent and Long-Running Updates	101
	Ratio of Stage-Concurrent Updates	102
	Pruning of Irretrievable Queries	103
	Effects of Long-Running Update and Queries during Runtime	103
	Related Work	104
	Conclusion	105
	References	106
	Near Real-Time Data Warehousing Using State-of-the-Art ETL Tools	107
	Near Real-Time Data Warehousing	107
	Related Work	108
	Data Wareh