Embracing Shift-Left in Data Architecture

In the rapidly evolving digital landscape, the way we approach data architecture is undergoing a transformative shift. This shift is not just about adopting new technologies but about fundamentally rethinking our approach to data management, governance and architecture design. Welcome to the concept of "Shift-Left Data Architecture" – a methodology that promises to set the foundation for future-ready data ecosystems.

As data's role in decision-making, operations and machine learning has become increasingly critical, the need for a more proactive approach has become evident. We need to reconsider traditional methods where data considerations, and supporting ML often came later in the development process, which led to inefficiencies, increased costs, and data quality and outcomes issues. By shifting left, organizations can avoid costly revisions, enhance data security, and ensure that their data architecture is robust and scalable.

Join us to learn more about this new era in data architectures, the building blocks of a shift-left architecture, the tools and technologies that enable it, and gain insights on how to implement these principles effectively within your organization.

From this track


OpenSearch Cluster Topologies for Cost-Saving Autoscaling

The indexing rates of many clusters follow some sort of fluctuating pattern - be it day/night, weekday/weekend, or any sort of duality when the cluster changes from being active to less active.  In these cases how does one scale the cluster?

Speaker image - Amitai Stern

Amitai Stern

OpenSearch PMC, Managing Observability Data Storage of Petabyte Scale @Logz.io


Stream and Batch Processing Convergence in Apache Flink

The idea of executing streaming and batch jobs with one engine has been there for a while. People always say batch is a special case of streaming. Conceptually, it is.

Speaker image - Becket Qin

Becket Qin

Principal Staff Software Engineer @LinkedIn


Beyond Durability: Enhancing Database Resilience and Reducing the Entropy Using Write-Ahead Logging at Netflix

In modern database systems, durability guarantees are crucial but often insufficient in scenarios involving extended system outages or data corruption.

Speaker image - Prudhviraj Karumanchi

Prudhviraj Karumanchi

Staff Software Engineer at Data Platform @Netflix

Speaker image - Vidhya Arvind

Vidhya Arvind

Staff Software Engineer @Netflix