Abstract

Over time, a number of people have brought in their input with the intention of enriching the lives of others positively.

The contributions of the study are aimed at enhancing the existing debate on the application of AI and data engineering through demonstration of the effective blend. For practitioners, the results act as a guide on how to adopt data engineering practices that improve PA systems’ performance reliability. For researchers, the study creates possibilities for other research to explore the relationship of emergent technologies and their efficiency in revolutionizing data flows.

Call to Action

Those organisations which are implementing AI solutions or have plans to do so should be aware of the central importance of data engineering to this effort. This way, they are able to develop more accurate and efficient as well as cheaper predictive analytic systems enabled by scalable, automated, and real-time data workflows. Stakeholders are urged to extend the findings of this research by examining more diverse sectors and forthcoming technologies to add new ideas and approaches to the field.