Paper Info
Title
Gradual data aggregation in multi-granular fact tables on resource-constrained systems
Abstract
Multi-granular fact tables are used to store and query data at different levels of granularity. In order to collect data in multi-granular fact tables on a resource-constrained system and to keep it for a long time, we gradually aggregate data to save space, however, still allowing analysis queries, for example, for maintenance purposes etc. to work and generate valid results even after aggregation. However, ineffective means of data aggregation is one of the main factors that can not only reduce performance of the queries but also leads to erroneous reporting. This paper presents effective methods for data reduction that are developed to perform gradual data aggregation in multi-granular fact tables on resource-constrained systems. With the gradual data aggregation mechanism, older data can be made coarse-grained while keeping the newest data fine-grained. This paper also evaluates the proposed methods based on a real world farming case study.
Year
DOI
Venue
2010
10.1007/978-3-642-15393-8_40
Lecture Notes in Computer Science
Keywords
Field
DocType
multi-granular fact table,gradual data aggregation,resource-constrained system,query data,newest data,gradual data,data aggregation,aggregate data,older data,data reduction
Data mining,Fact table,Computer science,Aggregate data,Granularity,Data aggregator,Database,Data reduction
Conference
Volume
ISSN
ISBN
6278
0302-9743
3-642-15392-5
Citations 
PageRank 
References 
6
0.53
9
Authors
2
Name
Order
Citations
PageRank
Nadeem Iftikhar18011.50
Torben Bach Pedersen22102181.24