Title

AWS re:Invent 2023 - New trends in data modernization: Catalysts for AI/ML analytics on AWS (ANT215)

Summary

The speaker, Sri, discusses the concept of data modernization and its evolution, emphasizing the need to move beyond simply transferring data to new platforms.
The talk covers the five tenets of data maturity: augmentation, awareness, availability, adaptability, and authenticity, and how their definitions have evolved.
Sri highlights the importance of data availability, not just in terms of access but also in terms of consumption and democratization, using AWS marketplace and data as a service.
The concept of authenticity is explored, with a focus on addressing data drift through synthetic data and AWS tools like Glue, Data Quality, and Data Brew.
The speaker stresses the need for industry-specific APIs and a data ethic framework, mentioning a framework called Ethica.
Data awareness is discussed, with an emphasis on the difference between data in rest and data in motion, and the need for a hybrid approach to data governance using AWS Data Catalog and third-party tools like Alation or Collibra.
Sri provides examples from various industries, including a global CPG company, a pharma company, and a large bank, to illustrate the application of these concepts.
The talk concludes with a case study of a telco client, highlighting the importance of centralized data governance, information factories, and parallel API development to reduce operational costs and improve business analytics.

Data modernization is not just about technology migration but also about redefining how data is used and consumed within an organization.
The shift in the definition of data availability from mere access to democratization and service-oriented access points to a need for a change in strategy towards data management.
The concept of data drift and the use of synthetic data to address it suggest that organizations need to anticipate changes in data behavior and adapt their models accordingly.
The development of industry-specific APIs and ethical frameworks like Ethica indicates a trend towards more tailored and responsible data management practices.
The distinction between data in rest and data in motion and the subsequent need for different governance strategies point to the increasing complexity of data management in real-time analytics.
The case studies presented demonstrate the practical application of AWS services and the importance of a holistic approach to data modernization that includes governance, ethics, and industry-specific solutions.
The emphasis on centralized data governance and the creation of information factories suggests a move towards more structured and efficient data management systems that can support advanced analytics and AI initiatives.
The talk underscores the importance of leveraging AWS's ecosystem, including services like AWS Marketplace, Glue, Data Catalog, Bedrock, and Neptune, to build a modern data platform capable of supporting AI/ML analytics.