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An Efficient Stochastic Update Propagation Method in Data Warehousing

An Efficient Stochastic Update Propagation Method in Data Warehousing

Bijoy Bordoloi, Bhushan Kapoor, Tim Jacks
Copyright: © 2018 |Volume: 29 |Issue: 2 |Pages: 19
ISSN: 1063-8016|EISSN: 1533-8010|EISBN13: 9781522542254|DOI: 10.4018/JDM.2018040102
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MLA

Bordoloi, Bijoy, et al. "An Efficient Stochastic Update Propagation Method in Data Warehousing." JDM vol.29, no.2 2018: pp.23-41. http://doi.org/10.4018/JDM.2018040102

APA

Bordoloi, B., Kapoor, B., & Jacks, T. (2018). An Efficient Stochastic Update Propagation Method in Data Warehousing. Journal of Database Management (JDM), 29(2), 23-41. http://doi.org/10.4018/JDM.2018040102

Chicago

Bordoloi, Bijoy, Bhushan Kapoor, and Tim Jacks. "An Efficient Stochastic Update Propagation Method in Data Warehousing," Journal of Database Management (JDM) 29, no.2: 23-41. http://doi.org/10.4018/JDM.2018040102

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Abstract

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.

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