Data Reliability Engineering: A New Approach to Data Quality | Bigeye

Slides: www.datacouncil.ai/talks/data...
ABOUT THE TALK
To remain competitive, modern organizations are operating ever-larger and more complex data platforms to support increasingly critical data use cases. For data engineering teams, this means it’s no longer sufficient to treat data quality problems like adhoc firefights. Instead, they need to take lessons from SRE and DevOps and treat data quality like an engineering problem - enter Data Reliability Engineering.
In this presentation, Egor Gryaznov, CTO and co-founder of Bigeye, will discuss Data Reliability Engineering and how this new approach addresses real-world use cases, including:
1. Building data reliability into your data pipeline orchestration.
2. Getting the data engineering team on the same page as their business counterparts in terms of expectations around the data.
3. Reducing the effort required to know when your data products are in a healthy state.
ABOUT THE SPEAKER
Egor is co-founder and Chief Technology Officer at Bigeye. Before starting Bigeye, Egor was a staff engineer at Uber where he scaled the company’s first data warehouse, supporting thousands of internal users and mission-critical workloads.
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[@datath]

Thank you! This is an awesome video

[@JavierDiazArca]

nice!

[@sashgorokhov]

Nothing practical

[@gustavoleo]

If something is very complicated, it often generates a lot of hype 🤔And also the password key Airbnb,LinkedIN and Uber