Enabling Hybrid Cloud Analytics & AI with Data Orchestration

The data ecosystem has heavily evolved over the past two decades with an explosion of data-driven frameworks, such as Presto, Spark, and Hive to run analytics and ETL queries and TensorFlow and PyTorch to train and serve models. On the data side, the approach to managing and storing data has evolved from HDFS to cheaper, more scalable and separated services typified by cloud stores like AWS S3. As a result, data engineering has become increasingly complex, inefficient, and hard, particularly in hybrid and cloud environments.
Join this upcoming webinar on August 5th at 2pm ET with Adit Madan, Technical Product Manager at Alluxio, for an overview of a data orchestration layer that provides a unified data access and caching layer for hybrid and multi cloud deployments. He'll review how it enables distributed compute engines like Presto, TensorFlow, and PyTorch to transparently access data from various storage systems (including S3, HDFS, and Azure) while actively leveraging a multi-tier cache to accelerate data access.