Data professionals are spending too much time on data prep, but the quality assurance that provides ensures projects are working with clean data
One particularly time-consuming and manual integration process step that could benefit from automation is data preparation.
As the volumes of data used in businesses grows, getting data suitably annotated and tagged to train machine learning models is an enormous challenge.
The first realization of that effort is a new AI Catalog from DataRobot, which makes it easier for business analysts and citizen data scientists to prepare …
Tackling the complex needs of manufacturing, energy and other big industrial clients, Splunk's latest IoT offering helps get your data ducks in a