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Data governance reference model under the lean methodology for the implementation of successful initiatives in the Peruvian microfinance sector

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Authors
Romero, Alvaro
Gonzales, Antony
Raymundo, Carlos
Issue Date
2019-04-09
Keywords
Data Governance
Framework
Lean
Microfinance

Metadata
Show full item record
Publisher
Association for Computing Machinery
Journal
ACM International Conference Proceeding Series
URI
http://hdl.handle.net/10757/656344
DOI
10.1145/3328833.3328859
Additional Links
https://dl.acm.org/doi/10.1145/3328833.3328859
Abstract
Microfinance allows the integration of all sectors for the country's economic growth. Data duplicity, invalid data and the inability to have reliable data for decision-making are generated without a formal Governance. For this reason, Data Governance is the key to enable an autonomous, productive and reliable work environment for the use of these. Although Data Governance models already exist, in most cases they don't meet the requirements of the sector, which has its own characteristics, such as the volume exponential growth, data criticality, and regulatory frameworks to which it is exposed. The purpose of this research is to design a reference model for the microfinance organizations, supported by an evaluation tool that provides a diagnosis with the objective of implementing and improving the organization processes regarding Data Governance. This model was implemented based on the information of Peru's microfinance organizations, from which a 1.72 score was diagnosed, which is encouraging for the organization, since it shows that it has defined all its plans concerning Data Governance. Finally, after the validation, it was concluded that the model serves as a medium to identify the current status of these organizations to ensure the success of the Data Governance initiatives.
Type
info:eu-repo/semantics/article
Rights
info:eu-repo/semantics/embargoedAccess
Language
eng
Description
El texto completo de este trabajo no está disponible en el Repositorio Académico UPC por restricciones de la casa editorial donde ha sido publicado.
ae974a485f413a2113503eed53cd6c53
10.1145/3328833.3328859
Scopus Count
Collections
Ingeniería de Sistemas y Computación

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