Review Article Open Access December 27, 2020

Improving Data Quality and Lineage in Regulated Financial Data Platforms

1
Senior Data specialist Data Engineering, USA
Page(s): 1-14
Received
September 28, 2020
Revised
November 21, 2020
Accepted
December 20, 2020
Published
December 27, 2020
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright: Copyright © The Author(s), 2020. Published by Scientific Publications
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APA Style
Davuluri, P. S. L. N. (2020). Improving Data Quality and Lineage in Regulated Financial Data Platforms. Current Research in Public Health, 1(1), 1-14. https://doi.org/10.31586/ujfe.2020.1366
ACS Style
Davuluri, P. S. L. N. Improving Data Quality and Lineage in Regulated Financial Data Platforms. Current Research in Public Health 2020 1(1), 1-14. https://doi.org/10.31586/ujfe.2020.1366
Chicago/Turabian Style
Davuluri, P S L Narasimharao. 2020. "Improving Data Quality and Lineage in Regulated Financial Data Platforms". Current Research in Public Health 1, no. 1: 1-14. https://doi.org/10.31586/ujfe.2020.1366
AMA Style
Davuluri PSLN. Improving Data Quality and Lineage in Regulated Financial Data Platforms. Current Research in Public Health. 2020; 1(1):1-14. https://doi.org/10.31586/ujfe.2020.1366
@Article{crph1366,
AUTHOR = {Davuluri, P S L Narasimharao},
TITLE = {Improving Data Quality and Lineage in Regulated Financial Data Platforms},
JOURNAL = {Current Research in Public Health},
VOLUME = {1},
YEAR = {2020},
NUMBER = {1},
PAGES = {1-14},
URL = {https://www.scipublications.com/journal/index.php/UJFE/article/view/1366},
ISSN = {2831-5162},
DOI = {10.31586/ujfe.2020.1366},
ABSTRACT = {Data quality and data lineage are critical concerns for organizations mandated to comply with stringent regulatory regimes. This paper analyses the latest developments in the governance of data quality and data lineage within a regulated financial services organisation. It sets out the underlying regulatory context, describes the concepts employed in the business environment, summarizes how data quality is captured and monitored, examines the artefacts that record data lineage, reviews the roles and responsibilities of staff who implement the necessary processes, and maps areas where improvements are possible. The internal organization and processes of regulated data platforms are shaped not only by the capabilities prescribed by their technical architecture but also by the regulatory regimes under which they operate. These mandates, in particular, require rigorous examination of four aspects of data quality — accuracy, completeness, consistency, and timeliness — and detailed documentation of how data arrives in its final form in the repository. Although data monitoring, alerting, assessment, and remediation are well established, provenance capture remains an area ripe for further investment.},
}
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AB  - Data quality and data lineage are critical concerns for organizations mandated to comply with stringent regulatory regimes. This paper analyses the latest developments in the governance of data quality and data lineage within a regulated financial services organisation. It sets out the underlying regulatory context, describes the concepts employed in the business environment, summarizes how data quality is captured and monitored, examines the artefacts that record data lineage, reviews the roles and responsibilities of staff who implement the necessary processes, and maps areas where improvements are possible. The internal organization and processes of regulated data platforms are shaped not only by the capabilities prescribed by their technical architecture but also by the regulatory regimes under which they operate. These mandates, in particular, require rigorous examination of four aspects of data quality — accuracy, completeness, consistency, and timeliness — and detailed documentation of how data arrives in its final form in the repository. Although data monitoring, alerting, assessment, and remediation are well established, provenance capture remains an area ripe for further investment.
DO  - Improving Data Quality and Lineage in Regulated Financial Data Platforms
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