Many enterprises just work at the edges of the toughest data problems and may not even realize how to tackle them. But some have managed to transform their organizations with the help of knowledge graphs. How did they succeed, and what can we learn from them?
What does real business transformation look like? In today's data-driven world, it's less and less about what applications you subscribe to, and more and more about the meaningful data that fuels the business directly, not to mention entire supply chains and ecosystems.
80 percent of a typical data scientist's time, according to Gartner, is spent just wrangling and cleaning data. That's not to mention data that should be reusable and shared cross-enterprise, if not cross-industry or openly. How do we make substantial corporate investments in content, analytics and AI pay off in a bigger way?
For many, a knowledge graph could be the centerpiece of a holistic business transformation strategy and key to that bigger payoff. This talk will review the fundamental knowledge graph-based architecture shift some companies have made and how it's cleared the path for business model changes, improved profitability, and a renewed focus on what's most critical to long-term success.