An analyst report offers an unbiased, side-by-side, third-party evaluation of the technology in the market. These analysts know how to put the vendors through the paces and require proof of any claims that are made.
Monthly Archives: October, 2020
The first principle of analytics is about bringing the right analytics technology to the right place at the right time. Whether your data are on-premises, in the cloud, or at the edges of the network – analytics needs to be there with it. Being true to this principle means we
SAS' Véronique Van Vlasselaer reveals why managing model performance is as important as putting them into production.
Discovery is an important part of setting up your analysis for success – essentially it prevents you from plunging into a haystack to try to find that elusive needle, and rather, helps you organize the haystack into neater, compact organized bales that you can navigate with ease. Proper discovery can help you more efficiently find patterns in your data set.
What does the AI enterprise of the future look like? That’s a tough question that I’ve been asked to consider, along with a distinguished panel at Valley ML AI Expo 2020. The title of the panel is, “Life, the Universe and the AI Enterprise of the Future.” Based on an initial chat with panel chair Gautam Khera, I’ve written up some possible topics we’ll be covering on the panel. Consider
“Technology is an industry that eats its young, it is rare to come across providers that have been around for more than a human generation.” Tony Bear, Big on Data With more than 40 years in the market, SAS is one of the rare technology providers that has been around
The model management process, which is part of ModelOps, consists of registration, deployment, monitoring and retraining. This post is part of a series examining the model management process, orchestrated through the Model Manager (MM) APIs. The focus of part one is on model registration, specifically on using the APIs from
A note from Udo Sglavo: The need for randomization in experimental design was introduced by the statistician R. A. Fisher in 1925, in his book Statistical Methods for Research Workers. You would assume that developing a successful treatment for COVID-19, the illness caused by the SARS-CoV-2 virus, will eventually conclude in