Sergey Lebedev

Optimized Data Lake Architectures for Scalable ML Workflows

The exponential growth of data and the increasing demand for real-time, large-scale machine learning (ML) applications have challenged traditional data storage and processing architectures. Data lakes have emerged as a flexible and cost-effective solution for storing massive amounts of heterogeneous data. However, with...