3 min read

Structured Data vs Unstructured Data | Igneous

By Catherine Chiang on July 31, 2018

For most of IT history, the focus of data protection and management has been on structured data. This is what most of us find familiar when we conceptualize “data”: numbers, strings, in neat rows and columns.

Topics: Machine Learning
4 min read

Is Your Infrastructure Scalable Enough to Tackle ML/AI Workflows?

By Lily Bowdler on June 26, 2018

As Allison mentioned in this blog post, scalability is an integral part of any infrastructure strategy that is going to deal with machine learning and artificial intelligence (ML/AI) workflows. Today, I’m going to delve a little bit further into why that is and how you can plan for it.

Topics: Machine Learning
3 min read

3 "Aha Moments" Enterprises Have While Planning Their AI Infrastructure Strategy

By Allison Armstrong on June 20, 2018

My last blog covered a few questions IT leaders are working on to best enable machine learning and AI projects.  

Topics: Machine Learning
1 min read

Let's Talk ML/AI at Big Data Toronto!

By Catherine Chiang on June 5, 2018

Team Igneous is headed to Big Data Toronto next week, June 12-13!

Topics: Igneous News Machine Learning
4 min read

Machine Learning's Impact on I&O Leaders

By Allison Armstrong on May 24, 2018

Machine learning…yes, it’s all over the industry press and every tech vendor uses the term in their marketing to jump into the chatter. So, here is yet another blog from another tech vendor on machine learning! Well, not quite.

Topics: Machine Learning
2 min read

Data Management Trends: Machine Learning, Artificial Intelligence, and High Performance Computing in the Life Sciences Industry

By Catherine Chiang on April 10, 2018

Explosive data growth in the life sciences industry is nothing new; what’s truly exciting is how this data can be used!

Topics: Igneous Solutions Machine Learning
8 min read

From Cave Walls to Billions of Files: The History of Data

By Tammy Batey on March 30, 2017

Remember that old philosophical question: If a tree falls in a forest and no one is around to hear it, does it make a sound? A modern version of that question might be: If data exists but no one is able to find it again or make sense of it, does it have value?

Topics: Industry Trends Backup and Archive Igneous Solutions Machine Learning AI

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