The video discusses the benefits of a centralized approach to data governance, where designated data creators ensure quality and privacy standards are met before data is made available for consumption. By limiting data generation to trained professionals and implementing robust quality control and privacy protections, organizations can foster trust and integrity in their data assets.
The video discusses the critical question of whether data creation and consumption should be open to everyone or if these roles should be separated. It highlights the challenges posed by the diverse nature of data sets, which come with varying quality and privacy thresholds across different use cases. The speaker suggests that a centralized approach may enhance trust in data management by limiting data generation to a select group of individuals who can ensure adherence to quality standards and privacy regulations.
In a centralized model, designated data creators would be responsible for generating data that meets established quality benchmarks. This group would collaborate closely with privacy and risk teams to ensure that all data is handled in compliance with privacy protections. By restricting data creation to trained professionals, the organization can maintain higher standards of data integrity and security.
Once the data meets the necessary quality and privacy criteria, it can be pushed to a cloud environment for downstream use. This process not only streamlines data management but also facilitates easier access for those who need to consume the data while ensuring that the data remains trustworthy and secure.
The video emphasizes that trust in data can indeed be established, provided that the right measures are in place. This includes implementing robust quality control processes, ensuring comprehensive privacy protections, and deploying data in a manner that safeguards its integrity. By focusing on these key areas, organizations can foster a culture of trust around their data assets.
Ultimately, the speaker advocates for a structured approach to data governance that prioritizes quality and privacy. By centralizing data creation and consumption roles, organizations can build a more reliable and trustworthy data ecosystem, which is essential in today’s data-driven landscape.