Research Article
Real-Time Monitoring of Data Pipelines: Exploring and Experimentally Proving that the Continuous Monitoring in Data Pipelines Reduces Cost and Elevates Quality
@ARTICLE{10.4108/eetsis.5065, author={Shammy Narayanan and Maheswari S and Prisha Zephan}, title={Real-Time Monitoring of Data Pipelines: Exploring and Experimentally Proving that the Continuous Monitoring in Data Pipelines Reduces Cost and Elevates Quality}, journal={EAI Endorsed Transactions on Scalable Information Systems}, volume={11}, number={4}, publisher={EAI}, journal_a={SIS}, year={2024}, month={2}, keywords={Data pipelines, monitoring, real-time, data observability, data quality, anomaly detection}, doi={10.4108/eetsis.5065} }- Shammy Narayanan
Maheswari S
Prisha Zephan
Year: 2024
Real-Time Monitoring of Data Pipelines: Exploring and Experimentally Proving that the Continuous Monitoring in Data Pipelines Reduces Cost and Elevates Quality
SIS
EAI
DOI: 10.4108/eetsis.5065
Abstract
Data pipelines are crucial for processing and transforming data in various domains, including finance, healthcare, and e-commerce. Ensuring the reliability and accuracy of data pipelines is of utmost importance to maintain data integrity and make informed business decisions. In this paper, we explore the significance of continuous monitoring in data pipelines and its contribution to data observability. This work discusses the challenges associated with monitoring data pipelines in real-time, propose a framework for real-time monitoring, and highlight its benefits in enhancing data observability. The findings of this work emphasize the need for organizations to adopt continuous monitoring practices to ensure data quality, detect anomalies, and improve overall system performance.
Copyright © 2024 S. Narayanan et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NC-SA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
