Today’s data landscape is complex, with more demands than ever to deliver value from data. Building a data architecture that empowers users and enables analytics and machine learning across the enterprise is a daunting task. With seemingly endless combinations of tools, storage considerations, and modern integration techniques to factor in, assessing applications and capabilities is an extensive process. One of the best ways to cut through marketing hype and understand what will work for you is hearing best practices from those who have gone before you.
Spend the morning walking through the success stories of four different organizations on their data platform quest. Hear about the hurdles they faced, how they overcame them, and their ultimate victories—and ask the questions that matter most to you.