Data science project failure can have a huge impact on a company’s bottom line, there are a number of factors that drive failure: Your data science project is not destined to fail (Gajus/Shutterstock) ...

A data science project related to customer segmentation could involve analyzing customer data from a retail company, such as transaction history, demographics and behavioral patterns.

Data science may be the hottest tool for solving business problems, but flawed projects can cause significant damage, leading decision-makers astray.

In my experience, data science projects fail not because of poor technology or lack of available data. Nor is it because of a lack of talent or technical skills. It's because of the last mile problem.

But if this is a universal understanding, that AI empirically provides a competitive edge, why do only 13% of data science projects, or just one out of every 10, actually make it into production?

Nino Letteriello is a data and project management leader, DAMA Award winner, WEF author, UN advisor, MIT lecturer & FIT Group co-founder. A significant percentage of data science projects continue ...

Ornithologists are seeking volunteers in California, Oregon and Washington for Project Phoenix, a multiyear project exploring ...

Capstone projects are academic semester-long experiences for students nearing graduation. Student teams complete a substantial data science project that solidifies knowledge gained in the classroom ...

Contrary to this assumption, survey responses (n=3,894) and digital trace data (n=3,649) from volunteers, who collectively engaged in 1,126 unique projects, revealed that multi-project ...