The evolution of a data platform

Designing a data platform is no easy task, particularly when there are new technologies, techniques, and approaches appearing every week. At Cox Auto UK we have been on a journey from manually deployed Hadoop clusters to a full platform as a service setup using Azure Databricks. This journey hasn’t always been smooth however and we’ve learned some things along the way! In this talk, we will examine how we have made design choices while evolving our platform, our decision to open source some of our work, and what our past, present, and future look like.

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James Fielder, Senior Data Engineer @ Cox Automotive

 

 

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What is Data Teams Summit?

Data Team Summit is the official DataOps peer-to-peer community.

It's a time each year for everyone, from DataOps, CloudOps, AIOps, MLOps, to other technology professionals, to gather virtually to share the latest trends and best practices for running, managing, and monitoring data pipelines and data-intensive analytics workloads.

Sessions include talks by DataOps professionals at leading organizations, detailing how they’re establishing data predictability, increasing reliability, and reducing costs.

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DataOps is a holistic approach to the creation, deployment, monitoring, management, and optimization of data-driven applications. It describes the culture and rules of engagement that allow data teams to deliver and maintain high-quality, on-time data products, often powered by AI and machine learning, in an agile and cost-effective way.

DataOps defines how data teams work and also affects data consumers and those whose work causes new data to be created and used within the organization. Their work enables the entire organization to access data efficiently for data-driven decision-making and for the creation and delivery of data-driven applications.

Organizations with well-developed DataOps strategies, governance, and processes can expedite the delivery of data-driven workflows and results faster and better than others.

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