Although, historically, the failure rate of data science projects has been high, it doesn’t mean that your organization’s projects should meet the same fate. In order to help mitigate the factors that ...

Analytics: Turning data science into business strategy (Free PDF) ... "People who know how to shape and execute projects, communicate to stakeholders, and explain why the work they've done matters." ...

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

Data Point No. 1: Lack of Resources to Execute Data Science Projects Data science is an interdisciplinary approach that involves mathematicians, statisticians, data engineering, software engineers ...

Data science needs room to experiment, but enterprise environments want everything production-ready from day one. This tension creates a massive roadblock to innovation. The Time-To-Market Challenge ...

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 ...

Data science plays a critical role in today’s academic landscape, with growing interest from students and professors outside of the traditionally associated fields of mathematics, computer science, ...

Here’s a rundown of some of the best newer or lesser-known data science projects available for Python. Some, like Polars, are getting more attention than before but still deserve wider notice.