Yet, for many companies, implementing data science into various aspects of their businesses can prove difficult if not daunting. According to Gartner analyst Nick Heudecker, over 85% of data science ...

A significant percentage of data science projects continue to fail. With the rise of artificial intelligence, we are witnessing similar failures and growing concerns about the return on investment ...

For example, one of his company’s early data science projects created size profiles, which could determine the range of sizes and distribution necessary to meet demand.

Overview: Free datasets are essential for practice, research, and AI model development.Platforms like Kaggle, UCI, and Google ...

These days every data project is a data-science project — and business stakeholders must take an active role in data science to realize the expected value.

That means using data ethically, involving citizens in the process, and building social values into the design. Here are a five data science projects that are putting these principles into: 1.

“Data-Driven Thinking” is written by members of the media community and contains fresh ideas on the digital revolution in media. Today’s column is written by Ellen Houston, managing director of ...

Design thinking is critical for developing data-driven business tools that surpass end-user expectations. Here's how to apply the five stages of design thinking in your data science projects.

That means using data ethically, involving citizens in the process, and building social values into the design. Here are a five data science projects that are putting these principles into practice.