Key Takeaways:

• Shift from static data lakes to real-time streaming to enable instant business responses, such as millisecond fraud detection, rather than relying on data at rest.
• Treat data as 10–15 high-value 'Data Products' with dedicated owners to drive specific financial outcomes instead of managing thousands of unorganized data sets.
• Adopt a 'Servant Leadership' mindset where your primary goal is setting your team up for success, which naturally leads to better organizational outcomes.
• Implement the 'Glad to be Here' philosophy from military debriefs, where every team member takes total accountability for mistakes and resets with a positive, grateful attitude.
• Avoid 'garbage in, garbage out' in AI by moving away from mass data dumping and focusing on high-quality, granular data streams to fuel generative models.
• Use data streaming to break down silos in healthcare for personalized patient alerts and in the automotive industry to leverage connected car telemetry.
• Frame every data initiative around three core objectives: whether it is making money, saving money, or protecting money.
• Lead change management by addressing the human element first, showing employees how technology transforms their roles into higher-level tasks rather than replacing them.