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September 18-19th

Prefect at Big Data LDN 2024

See you in the vendor hall or at one of our talks at Big Data London. Stop by early for an exclusive swag item!

(Spoiler: it's wearable and holds your valuables)

Highlighted Talks in London

Customer Story

Scaling Petabyte-Size ML Models Through Standardization at LiveEO with Prefect

Big data means big implications in terms of the cost of infrastructure and the complexity of running in production. LiveEO sells a data product based on Satellite imagery—a dataset that’s notoriously huge. To maximize their first-run success rate and therefore efficiency, LiveEO built a composable data platform to minimize failure, expose new data products faster to dependent teams, and scale efficiently.

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Resilience

Built to Fail: Design Patterns for Resilient Data Pipelines

Data is an open environment, and even the best code will break regularly due to upstream schema changes, flaky APIs, and poorly structured data. By embracing the reality of failure as a given, we can proactively architect our systems to minimize the impact of disruptions and ensure the continuity of our data operations. Attendees will learn practical techniques for anticipating specific failure modes and building resilient systems that can recover while minimizing the cost of problems.

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Learn About Prefect

Hear from our customers first hand.

Build Resilient Data Pipelines

Workflow Orchestration for the Modern Enterprise

From script to scale, Prefect's Python-based workflow orchestration platform delivers data workflows you can actually trust, resilient to failure and adaptable to change.

Build bulletproof data pipelines

Visualize and react to workflow execution paths and workflow-level metrics, capable of handling thousands of runs. Use metrics to trigger automatic alerts that drive faster remediation of errors.

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Scale efficiently with reliable architecture

Scale good practices efficiently to reduce maintenance burden and infrastructure cost. Integrate with Dask, Ray, and Kubernetes to build resilient data pipelines at any scale.

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