The promise of enterprise data platforms is compelling: a single source of truth that enables data-driven decision-making across the organization. The reality is often different - expensive platforms that sit underutilized because they were designed for data engineers, not for the business users who need the insights.
The most successful data platform initiatives we have seen start not with technology selection, but with user research. Understanding how analysts, operators, and executives actually consume data - and what decisions they are trying to make - is the single most important input to platform design.
Technical architecture matters, but it should follow use cases, not precede them. A well-designed data mesh or lakehouse architecture is meaningless if the people who need the data cannot find it, trust it, or access it in the format they need.
Organizations that get this right treat their data platform as a product, not a project. They assign product managers, measure adoption metrics, iterate based on user feedback, and invest in data literacy programs that help business users get value from the platform independently.