Ellen Friedman

Ellen Friedman is a principal technologist at HPE focused on large-scale data analytics and machine learning. Ellen worked at MapR Technologies for seven years prior to her current role at HPE, where she was a committer for the Apache Drill and Apache Mahout open source projects. She is a co-author of multiple books published by O’Reilly Media, including AI & Analytics in Production, Machine Learning Logistics, and the Practical Machine Learning series.

Secret ingredient to cloud: paving the way to private cloud

Unlocking the secret to scale-efficient systems: A clue from skyscrapers

Unlocking the secret to scale-efficient systems: A clue from skyscrapers

Take advantage of modern technological advances in data infrastructure and orchestration of computation to build a truly scale-efficient system.

How to Discard Data: Solving the Hidden Challenge of Large-scale Data Deletion

How to Discard Data: Solving the Hidden Challenge of Large-scale Data Deletion

In the modern, data-rich enterprise, having efficient and reliable ways to handle large-scale data deletion is essential. HPE Ezmeral Data Fabric does meets these requirements.

Two-Way Traffic at the Edge: A Guide for Edge to Core Computing

Two-Way Traffic at the Edge: A Guide for Edge to Core Computing

To better address the challenges of edge systems, it’s key to understand what happens at the edge, at the core, and in between.

Conquering hidden challenges of scale

Conquering hidden challenges of scale

You can’t win by solving a single challenge of scale: you need to uncover different aspects of the problem.

How to Afford Innovation

How to Afford Innovation

Consider these four strategies to make it reasonable to try innovative approaches.

Load More