Citation:

Santosh Kumar Singu, 2021. "Real-Time Data Integration: Tools, Techniques, and Best Practices", ESP Journal of Engineering & Technology Advancements 1(1): 158-172.

Abstract:

With the increase in information available, especially due to the embrace of the use of technology in the current generation, there has been an alteration in the ways data is used in businesses and organizations. It has been noted that real-time data integration has become highly valuable or critical in areas that require real-time or near real-time decision-making, including the finance, e-commerce, health care and manufacturing industries. In this paper, we are going to discuss about many tools and techniques as well as several best practices related to real-time data integration. The general objectives of real-time data integration revolve around synchronizing and harmonizing data in real-time across multiple systems as the data is being produced or modified in order to provide real-time perspectives into several business processes. Real-time data integration is always running and immediate compared to the batch processing integrating models, which are normal in other scenarios used in predictive analytics, fraud detection, personalization of customer services, and better functionality. Exploring a few of these techniques, the paper unveils the following: The ETL Framework It is a common integration of real-time data particularly for usage in data marts and warehouses. Further, it provides a detailed synthesis of real-time integration tools, including Apache Kafka, Apache Flink, Microsoft Azure Stream Analytics, and AWS Kinesis, among others. Additionally, ideas on ways that such corporations can enhance the significance of real-time data integration are described, including, amongst others, data validation, security considerations and scalability. Last, this paper delineates implications for the practice, limitations, future directions, and trends of the real-time data integration domain. In today’s world, which is gradually turning into the world of big data, real-time data integration will be a key factor in success.

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Keywords:

Real-time data integration, ETL, Change Data Capture (CDC), Streaming data, Apache Kafka, Apache Flink, Scalability, Data validation.