Paper Contents
Abstract
In the era of big data, efficient data integration and management are paramount for organizations seeking to harness the full potential of their information assets. This paper explores advanced techniques for data integration and management utilizing Azure Logic Apps and Azure Data Factory (ADF). Azure Logic Apps facilitate the automation of workflows, enabling seamless connectivity between disparate data sources and services. By leveraging pre-built connectors and custom APIs, Logic Apps streamline data transfer processes, reduce latency, and enhance operational efficiency. Meanwhile, Azure Data Factory provides a robust platform for orchestrating complex data workflows, enabling data ingestion, transformation, and loading (ETL) from a myriad of sources, including cloud and on-premises environments. The integration of these two powerful tools allows organizations to create a cohesive data ecosystem, promoting real-time analytics and informed decision-making. This paper examines various use cases, highlighting the implementation of data pipelines, automated data movement, and the application of best practices in designing scalable solutions. Additionally, we address the challenges associated with data governance, security, and performance optimization within Azure’s framework. Through detailed case studies, we demonstrate how businesses can achieve significant improvements in data accessibility, quality, and management efficiency. Ultimately, this study underscores the transformative impact of Azure Logic Apps and ADF on modern data strategies, offering a comprehensive roadmap for organizations aiming to advance their data integration capabilities.
Copyright
Copyright © 2023 Krishna Kishor Tirupati , Shreyas Mahimkar, Om Goel, Sumit Shekhar, Prof.(Dr.) Arpit Jain, Dr. Alok Gupta. This is an open access article distributed under the Creative Commons Attribution License.
