Data teams all have versions of the same complaints and challenges: unclear ownership, data produced with no clear continuing use, outdated processes, convoluted workarounds, and competing priorities. It can be easy to feel frustrated and that something has gone wrong, and it’s hard to break out of the day-to-day to diagnose and fix these issues.
This talk introduces data maturity models as a practical way to reframe those experiences as a normal part of organizational growth. Although no model maps perfectly onto every organization, these frameworks can help us recognize that many recurring data challenges are a part of normal organizational evolution. They provide a useful vocabulary for understanding and communicating where an organization is now, what capabilities are still developing, and what kinds of changes are realistic next steps.
This session is for anyone who works between business needs and data, at any career stage.
