Transforming Data Lakes into Intelligent Ecosystems: Applying AI for Enhanced Data Engineering Insights

Abstract

Data lakes have gained a strategic prominence in the contemporary society where data is the ultimate commodity. However, past data lakes have their problem with the inefficiency, data isolation, and decoupling of insightful information. However, to overcome these issues, the principles of AI bring an innovative solution. In this article, the author and I expand the concept of a data lake into an intelligent ecosystem where artificial intelligence will be integrated to improve data treatment procedures and perform complex analytics as well as business decision making. The embracing of Artificial intelligence and analytics can help the enterprises to analyze the huge set of structured and unstructured data and make consistent transformations to increase the capabilities of data processing enterprises. Based on the analysis of the case studies of companies from different industries, the role of machine learning, natural language processing, and predictive analytics for the further development of data lakes is considered in the article. Besides, the trends in data engineering and future directions of development in the field of AI as applied to the creation of self-controlled, self-organizing data environments are also discussed. This study provides evidence that, as AI is adopted concerning data lakes, it is effective not only in terms of operational efficiency but also find-able competitive advantages because of real-time and useful data insights. The author provides a summary of his finding and presents specific future implications for organizations seeking to incorporate AI into their existing data lakes, along with a brief Discussion of future studies directions in this rapidly growing field.