An Efficient Stochastic Update Propagation Method in Data Warehousing

This article develops a stochastic update propagation method for an operational data store (ODS) in data warehousing (DW) environments where data storage (and retrieval) is required as a sum of data at distributed source nodes. The authors' proposed method results in less network traffic (as co...

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Bibliographic Details
Published in:Journal of database management 2018-04, Vol.29 (2), p.23-41
Main Authors: Bordoloi, Bijoy, Kapoor, Bhushan, Jacks, Tim
Format: Article
Language:English
Subjects:
Analysis
Big Data
Business intelligence
Communications traffic
Computer networks
Computer peripherals industry
Customer relationship management
Data storage
Data warehouses
Data warehousing
Decision making
Forecasts and trends
Information systems
Literature reviews
Methods
Nodes
Propagation
Real time
Time lag
Citations: Items that this one cites
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Summary:This article develops a stochastic update propagation method for an operational data store (ODS) in data warehousing (DW) environments where data storage (and retrieval) is required as a sum of data at distributed source nodes. The authors' proposed method results in less network traffic (as compared with the real-time method) due to update propagation required because of changes in source data. More importantly, the method allows system users to place limits on the discrepancy between the source data and the ODS data that could result due to a time lag between source data changes and the update operation. Finally, the pre-specified limits on the discrepancy are maintained while accounting for two crucial factors in distributed systems: 1) some nodes are situated on more congested network links, and 2) some of the links on the network are less reliable. Real-time data propagation does not account for these frequently encountered networking concerns.
ISSN:1063-8016
1533-8010
DOI:10.4018/JDM.2018040102