How To Get Data Ready For AI Development
Search Data Management, Tuesday, November 26th, 2024
Factors including a combination of commitment to data quality, proper technology and pertinent processes are key to preparing data for feeding models and applications.
As enterprises' interest in developing AI tools rises, first making sure their data is ready to train models and applications is critical.
Getting data ready to inform AI tools, however, is not straightforward and simple. It takes a combination of committing to data quality, using proper tools and implementing appropriate organizational processes, according to according to a panel of experts speaking during Impact 2024, a virtual conference hosted by data observability specialist Monte Carlo in mid-November.