Financial institutions have invested heavily in data governance, infrastructure modernization, and analytics, yet many struggle with a vicious cycle of increasing complexity, inefficiencies, and eroding trust in their data. The symptoms include regulatory reporting struggles, data overload with limited usability, and failed centralization efforts. Traditional approaches to data management, such as Chief Data Officer functions and governance policies, have not solved real-world challenges, instead creating fragmented data ownership, poor data quality, and slow regulatory reporting. Modern data lakehouses offer improved performance but still struggle with batch analytics limitations and the need for specialized systems. The concept of data mesh, which aims to treat data as a product owned by business domains, has stalled due to unrealistic expectations and vendor misappropriation. Successful financial institutions are shifting toward a pragmatic, business-driven approach focused on defining data products, establishing data contracts, and implementing a unified access layer to manage their vast and diverse data ecosystems.