From in-memory computing to stream processing, machine learning, and AI -- the world of analytics is changing quickly. We spoke to Kelly Herrell, CEO of Hazelcast, to find out how these technologies will help enterprises make decisions more quickly.
- By James E. Powell
- December 6, 2019
Recent research has tried to create less biased algorithms, falsely represented ML accuracy, and shown how AI can be corrupted with bad data.
- By Upside Staff
- December 5, 2019
The popularity of AI and ML have wide-reaching effects on your enterprise. Here are three important trends driven by AI to look out for next year.
- By Ryohei Fujimaki
- December 2, 2019
The purpose of documenting data science and tips for judging the value of machine learning.
- By Upside Staff
- November 26, 2019
MinIO CEO and cofounder Anand Babu Periasamy explains why thinking about (and managing) data is so critical to enterprise success, the role of AI/ML, the disruptive nature of Kubernetes, and where analytics and data management are headed in 2020 and beyond.
- By James E. Powell
- November 26, 2019
Refined and labeled data is imperative for advances in AI. When your supply of good data does not match your demand, look to synthetic data to fill the gap.
- By Troy Hiltbrand
- November 22, 2019
Garbage training data in, garbage model out. Here are four things to address to solve data quality problems.
- By Brian J. Dooley
- November 21, 2019
Building a great machine learning team, removing data silos, and managing the structure of data governance organizations.
- By Upside Staff
- November 21, 2019