“To do AI well, you really have to have enterprise-grade data. And so you can think about it almost like a garbage in, garbage out problem. Whereas if you have crappy data, you don't have enterprise-grade data, you have quality issues, you don't have the ability to kind of integrate that full picture of your data and your business. You can expect to have crappy outcomes when it comes to AI as you're training these models. You can't expect to have high-quality outcomes as a result of this. So to me, data management and your data strategy and AI really go hand in hand for organizations.”
“You don't want to lose your agile edge as you grow as a company. And that's typically the curse of a large company, right? You get to a billion dollars or more as a business and you discover that your processes aren't really working for you and they start to really slow you down. You need to have that kind of architecture discipline, microservices architecture and an ability to bring all of those microservices together in an agile fashion to enable the business to keep up with the rate and pace of change that's going on.”
