In this digital world, data is an important asset; however, organizations are searching for storage solutions that will help them manage big data’s volume, latency, resiliency, and data access requirements. Traditionally, companies used existing tech stacks that delivered the same capabilities as a warehouse or lake but had adjustments in handling massive amounts of semi-structured data. These approaches often resulted in high costs and data duplication across all businesses. The emergence of data lake houses as a hybrid data architecture aims to deliver better benefits as it eliminates data silos, anticipating unified and Hadoop-based storage for analytics that could consolidate data storage and analysis.