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 ...

Art Hu, the global CIO of Lenovo, is one of the pioneers in the shift from project-to-product. He noted in a recent conversation that his organization grappled with the question of what to work on ...

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.

4. Product teams are diverse in talent and collaborative — each member plays a unique role in the product's success. Gartner noted that "by 2023, 80% of IT organizations will experience radical ...

Visualization and Reporting: Utilize tools to create clear reports and dashboards that show real-time ROI from data science projects, helping CXOs visualize the direct impacts on the organization ...

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 ...

MS in Data Science at CU Boulder The last decade has seen an explosion of data generation from individuals, businesses and institutions worldwide. As these organizations increasingly rely on ...

“If your competitors are applying AI, and they’re finding insight that allow them to accelerate, they’re going to peel away really, really quickly,” Deborah Leff, CTO for data science and ...

1. Support the hidden work that makes effective data science possible. Data scientists spend nearly half their time making sure their data is reliable, clean, and well organized. But too often, social ...

These facilitation tools can help you design a data innovation project. 3. Finding data translators and data therapists. Humanitarians and data people don’t usually speak the same language: they do ...