Building Intelligent Data Lakes: Leveraging AI in Data Engineering for Better Insights

Authors

  • Narendra Devarasetty Anna University 12, Sardar Patel Rd, Anna University, Guindy, Chennai, Tamil Nadu 600025, India Author

Keywords:

Artificial Intelligence (AI), Data Lakes, Data Engineering, Machine Learning, Predictive Analytics

Abstract

The proliferation of data in today’s digital age necessitates the development of intelligent data 
management solutions that can efficiently handle, process, and analyze vast quantities of 
information. This paper explores the integration of Artificial Intelligence (AI) with data 
engineering to build intelligent data lakes that offer enhanced data processing capabilities and 
deeper insights. Intelligent data lakes leverage AI to optimize data ingestion, storage, and retrieval 
processes while employing advanced analytics and machine learning techniques to uncover 
actionable insights. This study investigates the key components of AI-driven data lakes, including 
automated data integration, real-time analytics, and predictive modeling. By examining case 
studies and real-world applications, we illustrate how AI can transform traditional data lakes into 
dynamic and intelligent systems capable of supporting complex decision-making processes. The 
paper also discusses the challenges and best practices for implementing AI-driven data lakes, 
highlighting the importance of data quality, scalability, and security. The findings provide valuable 
guidance for organizations seeking to harness the power of AI to enhance their data engineering 
practices and derive more meaningful insights from their data assets. 

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Published

2023-05-09

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