The author predicts that big data will be a major focus in 2025 due to the increasing reliance on generative AI. As AI models require vast amounts of data to function effectively, the need for high-quality and timely data will become even more critical.
It’s that time of year again, when people publish their top-10 or top-20 lists of what to expect in the year ahead. As usual, rather than pile on with another list, I’m limiting my contribution to one compelling (or half-baked) trend for the year ahead. In the year ahead, big data will be back. Data is becoming more than the new oil, it is becoming the new money.
Big data, which became a big deal about a decade ago as analytics hit center stage as the path to business success, faded a bit as big data suddenly was everywhere, making the term irrelevant. Over the past two years, amid all the excitement about generative AI, it almost seemed as if data — or attention to its quality and trustworthiness — took a back seat to all the jazzed-up illustrations and hyper-insightful insights generative AI was delivering. Now, with genAI so critical to business, people are realizing that their AI foundations are built on piles of very loose sand. When AI “hallucinates,” it’s not because it’s mind is wandering, because it has no mind to speak of. It’s simply running probabilities to grab on to the next piece of available and related data to complete a narrative. Now, there’s even concern that we’re starting to run out of data to feed the machines. “Most of the world's publicly available data — whether it is obtained legally or not — has been exhausted,” said So, yes, data will very much be back in the spotlight in 2025, because we need it, lots of it, and it has to be really good and really timely., principal at dbInsight.'As cloud scale made big data the norm, we began taking data, and managing lots of it, for granted. Then genAI burst on the landscape last year, and the venture funds began chasing AI with a vengeance.”out of Qlik. “Big data analytics leverages AI for better data analysis. In turn, AI requires a massive scale of data to learn and improve decision-making processe
BIG DATA GENERATIVE AI DATA ANALYTICS AI DEVELOPMENT DATA QUALITY
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