Treffer: Designing Data Governance for the Future: Privacy, Stewardship, and Intelligent Control.

Data governance is challenged by issues that, at least for the most part, were not anticipated a decade ago. Privacy expectations have evolved beyond what standard frameworks are able to handle. The interdependence of data has gotten so complex that it is not feasible to supervise it by hand anymore. Most organizations still depend on stewards who manually classify datasets and assign permissions. This creates bottlenecks that slow down business operations. Controls get implemented inconsistently across different departments. Transparency remains elusive when data moves through multiple systems. What organizations really need now are governance models built around ethical data use from the ground up. Identity management needs to be unified across all platforms. Quality checks should run automatically instead of relying on human review. Access policies must drive themselves based on clearly defined rules. Privacy protections can't be optional add-ons anymore - they need to be baked into system designs. Data should only be kept as long as necessary. Consent forms need to use plain language that people actually understand. When data gets shared, it has to be done responsibly with proper safeguards. Metadata intelligence can automate the classification work that takes humans forever. Lineage tracking shows exactly where data comes from and where it goes. Quality scores provide everyone with a neutral manner of determining whether data is suitable for use. Good governance is not a barrier to innovation; on the contrary, it is a facilitator. If teams trust the data, they will have more freedom to make quick decisions. Compliance stops being a constant firefight and becomes part of normal operations. Organizations that get this right will outperform competitors who are still stuck in manual governance mode. [ABSTRACT FROM AUTHOR]