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.

We have also seen data breaches, compliance challenges and M&A activity to monetize data, many times to the detriment of consumers. How do brands redress the balance? By earning back the trust.

AI is surging. Quantum is maturing. Data centers have moved from back-end utilities to frontline strategic infrastructure.

To gain business value from data, enterprises need to get their data architecture right – and the right business leadership and culture is critical to that.

Sustainability must be embedded in every stage of AI data center design – treating it as an afterthought will only lead to inefficiencies and missed opportunities.

How can we reap the benefits of big data while minimizing risks? Dr. Christopher Worsham and Dr. Anupam Jena offer some guiding principles.

The statement is an idealistic one – the probability that a Data Center, with its need for massive amounts of electricity, power backups, and telecommunications infrastructure, could be designed ...

Up to 73 Percent of Company Data Goes Unused for Analytics. Here’s How to Put It to Work Targeting the right areas and using the right technology can save your bottom line.

We’ve seen how fully remote work can lead to a loss of connection and development opportunities, particularly those that require observational learning, or learning by watching someone else do ...

How Do You Design a Better Hospital? Start With the Light A new trend in patient-centered design focuses on making environments more comfortable and less scary.