846: Making Enterprise Data Ready for AI — with Anu Jain and Mahesh Kumar

Governance Issues

The current state of data governance is fraught with challenges, including technical debt and centralization issues. Mahesh Kumar explains that traditional governance models are often seen as "ivory tower" structures, where decisions are made by committees without practical implementation at the data level 1. This centralized approach is becoming obsolete as data becomes more decentralized. Anu Jain adds that many organizations struggle with outdated infrastructures and the inability to track data from source to application, leading to inefficiencies 2.

Data governance, like I say, everyone talks about it, but no one's really doing it today.

--- Anu Jain

To address these issues, adopting a composable architecture with open standards is crucial, allowing for automation and visibility in governance processes 2.

   

Decentralization

Decentralization is reshaping data governance, emphasizing the need for infrastructure agnosticism and open standards. Mahesh Kumar highlights the importance of being able to operate across various data platforms without being locked into a single vendor, which allows for greater flexibility and cost efficiency 3. Anu Jain supports this by noting that the real cost lies in data compute rather than storage, advocating for the decoupling of compute from storage to enhance portability and efficiency 1.

Governance has to sort of metaphorically move with the data.

--- Mahesh Kumar

This shift towards decentralized governance requires a new architecture that can apply appropriate rules and policies directly where the data is used, ensuring compliance and ethical use 1.