Data Analytics Automation with AI: A Comparative Study of Traditional and Generative AI Approaches

Authors

  • Prabu Ravichandran Sr. Data Architect, Amazon Web services, Inc., Raleigh, USA Author
  • Jeshwanth Reddy Machireddy Sr. Software Developer, Kforce INC, Wisconsin, USA Author
  • Sareen Kumar Rachakatla Lead Developer, Intercontinental Exchange Holdings, Inc., Atlanta, USA Author

Keywords:

Data Analytics, Artificial Intelligence, Generative AI

Abstract

Data analytics enabled by AI replaced previous methods. Generative AI and analytics replace conventional data analytics. Traditional data analytics uses computers and humans to get insights. These solutions lack scalability, flexibility, and accuracy in large, complicated datasets or fast-changing business settings. 

Generative AI improves analytics. Variational Autoencoder and GAN create new data or patterns from existing data. Synthetic data improves model training, projections, and missed insights. Generator AI helps complex data analytics organizations. 

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Published

26-07-2023

How to Cite

[1]
Prabu Ravichandran, Jeshwanth Reddy Machireddy, and Sareen Kumar Rachakatla, “Data Analytics Automation with AI: A Comparative Study of Traditional and Generative AI Approaches”, Journal of Bioinformatics and Artificial Intelligence, vol. 3, no. 2, pp. 168–191, Jul. 2023, Accessed: Apr. 28, 2025. [Online]. Available: https://jbaijournal.org/index.php/jbai/article/view/1