Jason Smith, Chief Technology Officer, AI & Analytics at Within3, highlights how many life science data sets contain unclean, unstructured, or highly-regulated data that reduces the effectiveness of AI models. Life science companies must first clean and harmonize their data for effective AI adoption.
The Problem with ‘Dirty Data’ — How Data Quality Can Impact Life Science AI Adoption
June 15, 2023 by
Avoiding the Negative Impacts of Dirty Marketing Data
April 12, 2021 by
In this contributed article, Sky Cassidy, CEO of MountainTop Data, highlights how consumers are interested in receiving relevant, meaningful messages but too often the data base a company relies on is filled with incorrect and inconsistent information – meaning those messages are lost. Dirty data can have a negative effect on a company’s bottom line, with some business leaders estimating erroneous online accounts have cost them 12% of their overall revenue.
