The data lakehouse paradigm

The data lakehouse paradigm combines the best aspects of the data warehouse with those of the data lake. A data lakehouse is based on open standards and implements data structures and data management features such as data warehouses. This paradigm also uses data lakes for its cost-effective and scalable data storage. By combining the best of both data warehousing and data lakes, data lakehouses cater to data analysts and data scientists simultaneously, without having to maintain multiple systems or having to maintain redundant copies of data. Data lakehouses help accelerate data projects as teams access data in a single place, without needing to access multiple systems. Data lakehouses also provide access to the freshest data, which is complete and up to date so that it can be used in BI, data science, machine learning, and AI projects. Though data lakehouses are based on data lakes such as cloud-based object stores, they need to adhere to certain requirements...