Enhancing Data Engineering Frameworks for Scalable Real-Time Marketing Solutions

Balachandar Paulraj

doi:10.55544/ijrah.3.5.34

Authors

Balachandar Paulraj Independent Researcher, USA

DOI:

https://doi.org/10.55544/ijrah.3.5.34

Keywords:

Scalability, Real-time Analytics, Data Pipeline Optimization, Big Data Processing

Abstract

This report discusses improvements to the data engineering frameworks for cost-efficient real-time marketing environment, with the applications in mobile advertising and smart city analytics. The proposed framework combines the processing of time-series data with map-reduce (M-R) systems in order to compensate for inefficiencies in the execution of temporal queries and the processing of real-time data streams. It enables effective behavioral targeting in mobile marketing and helps integrate various domains’ real-time data for smart city utilization. Specific examples that illustrate further refinements in the algorithms are showcased through case study and experimental evidence where gains in throughput, data reliability, and system effectiveness are quantified in real-time Marketing and Smart City applications.

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