Driving DataOps Culture with LinkedIn DataHub
Your data is not changing slowly, so why should your metadata?
LinkedIn DataHub was open-sourced to enable other organizations to harness the power of metadata and unleash excellent DataOps practices. Doing DataOps well requires bringing together multiple disciplines of data science, data analytics, and data engineering into a cohesive unit. However, this is complicated, because there are a wide variety of data tools that are in use by these different tribes. Shirshanka, who founded and architected DataHub at LinkedIn, will describe its journey in enabling DataOps use-cases on top of the metadata platform. He will also showcase the latest integrations and features in the tool and share the roadmap for the project.
Shirshanka Das, Co-Founder & CTO @ Acryl Data
My mission is to make engineers productive with data, ethically. I am a technical lead in the Data team at LinkedIn. I like solving large scale challenges in distributed data systems. I've built several data infrastructure projects at LinkedIn, some of which are open source: Apache Helix, Espresso and Databus.
I'm involved in the following projects aimed at simplifying the big data management space: Apache Gobblin (incubating), LinkedIn DataHub, Apache Pinot (incubating) and Dali.
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Data Team Summit is always free and open for all to attend.
When is Data Teams Summit 2024?
Data Teams Summit 2024 was held on January 24, 2024.
What is Data Teams Summit?
Data Teams Summit is an annual peer-to-peer day of empowerment for data teams that reflects our focus on the teams and individuals running, managing, and monitoring data pipelines.
Data Teams Summit is a full-day virtual conference, led by real-world data practitioners and leaders at future-forward organizations about how they're establishing predictability, increasing reliability, and creating economic efficiencies with their data.
Who comes to the Data Teams Summit?
Data professionals and experts including data engineers, administrators, architects, analysts, AI/ML professionals, and relevant data technology leadership.
Join us for sessions on:
- Data teams and the way they work together
- Data pipeline, infrastructure & application performance
- Data quality, management & data governance strategy
- Methodology that allows teams to move faster and more efficiently
- DataOps/MLOps/AIOps/FinOps
- Data modernization & transformation
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