Efficiency and Agility for a Modern Solution of Deterministic Multiple Source Prioritization and Validation Tasks

Cesaro Annalisa () and Tininini Leonardo ()
Additional contact information
Cesaro Annalisa: Italian National Institute of Statistics (Istat), via Balbo 16, 00184Roma, Italy.
Tininini Leonardo: Italian National Institute of Statistics (Istat), via Balbo 16, 00184Roma, Italy.

Journal of Official Statistics, 2018, vol. 34, issue 4, 825-862

Abstract: This article focuses on a multiple source prioritization and validation service. We describe a modern rule-based, loosely coupled solution. We follow generalization, efficiency and agility principles in application design. We show benefits and stumbling blocks in micro-service architectural style and in rule-based solutions, where even the selection task is solved through selection rules, which encapsulate the calls to Entity Services, allowing access to input-sources. We allowing the rule-based service efficiency and further local and remote input data selection scenarios for the validation Statistical Service. In particular, data virtualization technologies enable architects to use remote sourcing and further increases agility in data selection issues. Through a wide number of experimental results, we show the necessary level of attention in process implementation, data architectures and resource usage. Agility and efficiency emerge as drivers which possibly sustain the Modernization flexibility impetus. In fact, flexible services may potentially serve multiple scenarios and domains.

Keywords: Rule engine for validation and prioritization; highly-performant data management; efficient data parallelism; data virtualization; agile culture (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations:

Downloads: (external link)
https://doi.org/10.2478/jos-2018-0042 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:vrs:offsta:v:34:y:2018:i:4:p:825-862:n:3

DOI: 10.2478/jos-2018-0042

Access Statistics for this article

Journal of Official Statistics is currently edited by Annica Isaksson and Ingegerd Jansson

More articles in Journal of Official Statistics from Sciendo
Bibliographic data for series maintained by Peter Golla ().