In this post, we talk about design process of a serverless data lake using cloud-native technologies.
Have you ever dreamed of a data platform that allows you to:
Maintain versions of data sets used to train Machine Learning (ML) models;
Provide full audit log to any changes made to the data;
Have ACID (Atomicity, Consistency, Isolation, Durability) transactions in your data lake;
Enables schemas to help with data quality;
Handles metadata with ease?