The News: HPE has acquired Pachyderm, a startup that offers open source-driven software to help automate and improve the value of large-scale data-fed machine learning pipelines in almost any industry. According to HPE, the long-term plan is to integrate Pachyderm software with HPE’s current supercompute / AI offerings. The Pachyderm purchase comes less than a year after HPE invested in the company last February via its venture capital arm, Hewlett Packard Pathfinder. Read the full announcement from HPE here.
HPE Gives a Bump to AI-at-scale with Pachyderm Acquisition
Analyst Take: Data is an important commodity. And as we have hear continuously for the past decade or more, the company that helps businesses gain better, faster insights from data at scale will win the game. It’s this, along with the desire to build an everything as a service offering (XaaS) that can compete with hyperscale cloud providers, that has propelled HPE into investing so heavily in things like AI, the IoT, distributed computing and other high-margin technologies. HPE has made several different acquisitions over the past few years to add to its capabilities, and this acquisition of Pachyderm is just the latest that will make a difference for their customers. A list of HPE’s other recent acquisitions can be found here.
What we like about Pachyderm — and HPE’s acquisition of it — is that is software can be used by almost any company, anywhere. Whether a business is working in healthcare, finance, or agriculture, it can streamline complex data pipelines in tighter, more value-driven ways acting as an enabler for enterprises to effectively utilize machine learning. With HPE’s reach, we believe it will be able to help Pachyderm scale and commercialize further. HPE’s investment in Pachyderm will help HPE bring new AI-at-scale opportunities to customers via its HPE Machine Learning Development Environment. The combined HPE-Pachyderm tech is already being utilized by Lockheed Martin as part of its open-architecture AI-at-scale project, AI Factory.
AI-at-scale is Giving Companies an Advantage
It used to be that automation at-scale was the next big thing. Today, AI-at-scale is what companies are striving for to gain a competitive advantage while also improving customer trust. Being able to more rapidly reproduce an ML pipeline enabling businesses to use the same dataset to get the same results each time. This helps build transparency, accuracy, and trustworthiness in ML predictions. Overall, I see a lot of potential in this deal by HPE as the company continues to expand its portfolio into data services for its GreenLake portfolio.
Disclosure: Futurum Research is a research and advisory firm that engages or has engaged in research, analysis, and advisory services with many technology companies, including those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.
Analysis and opinions expressed herein are specific to the analyst individually and data and other information that might have been provided for validation, not those of Futurum Research as a whole.
Other insights from Futurum Research:
Why Edge-to-Cloud Platform? Why HPE? – New Futurum Research Report
Protecting the Enterprise with an Edge-to-Cloud Security Strategy – HPE Executive Insights Series
HPE Revenue Hits $7.87B in Q4, Beating Analyst Estimates
Image Credit: HPE
Author Information
Daniel is the CEO of The Futurum Group. Living his life at the intersection of people and technology, Daniel works with the world’s largest technology brands exploring Digital Transformation and how it is influencing the enterprise.
From the leading edge of AI to global technology policy, Daniel makes the connections between business, people and tech that are required for companies to benefit most from their technology investments. Daniel is a top 5 globally ranked industry analyst and his ideas are regularly cited or shared in television appearances by CNBC, Bloomberg, Wall Street Journal and hundreds of other sites around the world.
A 7x Best-Selling Author including his most recent book “Human/Machine.” Daniel is also a Forbes and MarketWatch (Dow Jones) contributor.
An MBA and Former Graduate Adjunct Faculty, Daniel is an Austin Texas transplant after 40 years in Chicago. His speaking takes him around the world each year as he shares his vision of the role technology will play in our future.
