Streamlining ROP Metrics and Reporting through Cloud Migration and Automation
DOI:
https://doi.org/10.15662/IJARCST.2024.0704015Keywords:
ETL, Informatica PowerCenter, Azure Data Factory, CI/CD Processes, Jenkins, GitHubAbstract
This document outlines an innovative methodology for modernizing ETL (Extract, Transform, Load) pipelines by embracing the use of automation, cloud migration methods, performance monitoring, and data architecture with respect to business requirements. The document describes how scalable cloud-native ETL operations using Informatica PowerCenter and Azure Data Factory can replace outdated SSIS packages, under the automation interface of Control-M. The document discusses how to support high-quality data delivery in a timely manner with structured ETL testing methodology and CI/CD processes using Jenkins and GitHub. The next part of the document recommends the benefits of using Power BI for the purpose of analytics, reporting and visualization in a data enabled decision-making process. Effective collaboration with global teams is established to successfully deliver using agile and scrum project management methodologies. Key performance indicators such as throughput, latency, error rates and resource utilization provide insight to tunnel health and where there could be improvements. The paper outlines a general framework for creating dependable and intelligent data pipelines in a volatile, data-centered economic context, and outlines trending on the horizon trends, such as AI driven automation, real-time streaming ETL models and advances in engineering and governance.
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