Year: 2025
Type: article
Abstract: This article explores how organizations can leverage Lakehouse technology to build robust AI-ready data strategies. Lakehouse architecture represents a paradigm shift in data management by unifying data lake flexibility with data warehouse reliability. The integration of this technology enables organizations to overcome traditional barriers to AI implementation through unified storage, efficient processing, and comprehensive governance. By examining key components including data ingestion, preparation, metadata management, governance, and scalable infrastructure, the article illustrates how Lakehouse technology establishes a foundation for advanced AI applications like predictive analytics, recommendation systems, natural language processing, and automated decision-making. The article addresses common implementation challenges and provides solutions for data governance, quality assurance, infrastructure scaling, and integration with AI/ML tools, offering organizations practical guidance for transforming their data infrastructure into a catalyst for AI innovation.
Author: Jyoti Aggarwal
Institution: Carnegie Mellon University
Language: English
Subfield: Management Information Systems
Domain: Social Sciences
Open Access status: diamond
OpenAlex ID: W4410186836