In
2006, a young engineer at a rising e-commerce startup noticed a glaring
inefficiency. His company had an enormous amount of customer data—every click,
every search, every purchase—yet their business decisions relied mostly on
intuition. What if, he wondered, they could harness this data intelligently to
predict customer needs before they even realized them? This insight wasn’t just
a passing thought; it was the spark that helped revolutionize AI-driven
decision-making, laying the foundation for modern data platforms.
Today, companies like Amazon, Tesla, and Google are leading the AI revolution, not just because they have the best algorithms, but because they have the best data platforms. AI without quality data is like a race car without fuel—it won’t go anywhere. Yet, despite the promise of AI, an astonishing 87% of AI projects never reach full production. The biggest roadblock? Data.
