Simplified Data Preparation for Machine Learning in Hybrid and Multi Clouds

ODSC WEST 2019 Cloud storage brings great flexibility in management and cost-efficiency to data scientists, but also introduces new challenges related to data accessibility and data locality for machine learning applications. For instance, when the input data is stored in a remote cloud storage like AWS S3 or Azure blob storage, direct data access is … Continued

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What can I do to speed up analytics performance on remote data?

Background Today’s advanced analytics applications run on more datasets that ever before. The locations of where data “lands” is becoming more dispersed. And the separation of compute and storage in modern environments lends well to running on these distributed datasets. Data can be stored in a remote location from the compute, such as in a … Continued

Accelerating Analytical Workloads for Public & Hybrid Clouds

New York Meetup *

In this meetup, Dipti and HY will present a new approach to hybrid analytical workloads using Alluxio, an open source data orchestration layer, which sits between compute and storage layer. Applications like Apache Spark or TensorFlow can then seamlessly access multiple disparate data sources with consistent performance using data locality and abstraction that the data orchestration tier brings.