Manufacturers operate some of the most complex machinery on the planet – from CNC machines and industrial robots to gas turbines with over 20,000 components. Keeping these assets running smoothly is mission-critical, yet maintenance teams are often buried under vague alerts, scattered documentation and time-consuming root cause analysis. Much of
Most analytics stories don’t start with technology. They start with a moment of friction. A meeting where two dashboards disagree. A decision that feels urgent, but the data arrives too late. A report that technically answers a question but doesn’t inspire confidence. That’s usually when organizations realize they don’t just
Building a machine learning pipeline in SAS® Model Studio is rarely a straight line. You start with a goal in mind but quickly find yourself navigating many decisions: understanding the nuances of your data, identifying and fixing data quality issues, choosing models for the task and evaluating training results to
This is the final post in a five-part blog post series that delves into modernizing marketing strategies through the integration of advanced marketing platforms. I had the pleasure of interviewing Shaun Memon of Munvo for this series, where we discuss a wide range of topics, from fragmented MarTech stacks, first-party
Every so often, new technology hits like an earthquake. It starts with faint rumblings, then suddenly creates an irreversible shift in the landscape. Social media was one of those moments. What began as an experiment quickly became a cultural engine, reshaping how we communicate, consume information and do business. Its
Cybersecurity programs are often judged by what goes wrong. However, the most effective security teams are defined by what remains invisible to customers: disciplined preparation, swift decision-making and a clear understanding of where risk truly matters. At SAS, cybersecurity is treated as a business enabler rather than a reactive control
If AI engineering is the connective tissue, what exactly does it connect? In part one of this series, I made the case that AI engineering isn't just another buzzword – it's a discipline that integrates the technical, ethical and human dimensions of building AI systems. So, what are we connecting,
Now that AI has entered the business world, I believe the next stage involves combining AI technology with significantly greater computing power. Quantum AI represents the next step, opening up exciting prospects for organizations by enabling speed, precision, efficiency and innovation in areas where classical technology reaches its limits. Traditional
Technology advances fast, but meaningful innovation still comes down to one truth: systems work best when they’re built around people. In risk, fraud, and compliance (RFC), this means designing tools that understand intent, reduce friction for investigators, protect sensitive data, and adapt as fraud evolves. The Grace Hopper Celebration (GHC)
As energy systems become more distributed, digital and dynamic, utilities are increasingly turning to AI and IoT to help modernize operations, improve reliability and accelerate decarbonization. Yet according to the IDC InfoBrief, How AIoT Is Reshaping Industrial Efficiency, Security, and Decision-Making, more than half of AIoT initiatives are still stuck in
