Waynette Tubbs is a seasoned technology journalist specializing in interviewing and writing about how leaders leverage advanced and emerging analytical technologies to transform their B2B and B2C organizations. In her current role, she works closely with global marketing organizations to generate content about artificial intelligence (AI), generative AI, intelligent automation, cybersecurity, data management, and marketing automation. Waynette has a master’s degree in journalism and mass communications from UNC Chapel Hill.
This technical case study by Faisal Dosani, Royal Bank of Canada; Lisa Eckler, Lisa Eckler Consulting Inc.; and Marje Fecht, Prowerk Consulting Ltd., discusses the steps to develop a hands-off process for creating flexible and extensible solutions that avoid maintainability issues and enable speed to market of results. Building reusable
The traditional methods of making credit decisions relied mostly on human judgment; those have been replaced by methods that use statistical models. Today, statistical models are used not only for deciding whether to accept an applicant (application scoring), but also to predict the likelihood of defaults among customers who have
Big data seemed like all of the other marketing hype that we hear. But as the months have gone by, it seems clear that everyone is dealing with big data. You know, data coming in so fast that you can't adequately analyze it (at least not as efficiently and quickly
