Title

AWS re:Invent 2023 - Modern data governance customer panel (ANT206)

Summary

The session focused on treating data as a differentiator for funded business initiatives and the necessary skills for understanding, curating, and protecting data.
Experts Gabe from Semper California, Mirko from Natera, and Ruben from BMW shared their experiences and knowledge.
The discussion centered around AWS's three pillars for data: adaptability, integration, and data governance.
Data governance was broken down into finding and accessing data, keeping it secure, and enabling controls.
The panelists emphasized the importance of changing the perception of data governance from bureaucratic to an enabler of innovation.
They discussed the need for understanding data context, curating data for various use cases, and protecting data while considering compliance and lifecycle management.
The importance of organizing people and processes to ensure successful data governance was highlighted.
The concept of data as a lifestyle within an organization was introduced, emphasizing the need for quick wins, measurable business impact, and a sustained long-term approach.
The panelists shared their company-specific approaches to data governance, including the use of data mesh architecture, federated models, and the importance of balancing empowerment with accountability.
The session concluded with a discussion on hot topics like innovation acceleration, new business models, and generative AI, along with resources for getting started with data governance.

Data governance is evolving from a traditional, slow-moving process to a dynamic enabler of innovation, especially with the advent of generative AI.
Organizations are moving towards a federated model of data governance, where responsibility is decentralized, and teams closer to the business manage their data.
The concept of data mesh is gaining traction, emphasizing the importance of integrating data once and allowing for indefinite consumption.
Companies are increasingly treating data as a product, which requires careful consideration of data quality, compliance, and access control.
There is a shift towards serverless architectures and composable components in data governance to increase trust and speed up innovation.
The role of AI, such as the introduction of Maya at BMW, is becoming more prominent in automating metadata management and improving user interaction with data governance tools.
AWS offers resources like a masterclass on data governance, a data maturity assessment, and workshops to help organizations elevate their data governance practices.