Fueling innovative software
July 15-18, 2019
Portland, OR
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Jiaqi Liu

Jiaqi Liu
Lead Software Engineer, University of Chicago, CTDS

Jiaqi Liu is a Lead Software Engineer at the Center for Translational Data Science at the University of Chicago. Previously she was Tech Lead at Button and Data Scientist at Capital One Labs. She is passionate about bridging the gap between the science and engineering part of data-driven work and champions inclusivity in the workplace, and advocates for a culture where everyone’s input matters. She is also active in the Write/Speak/Code and Women Who Code communities.he’s a director at Women Who Code NYC.

Sessions

1:45pm–2:25pm Thursday, July 18, 2019
Observability for data pipelines: Monitoring, alerting, and tracing lineage
Building Data-Intensive Applications
 Location: E143/144
Secondary topics:  Data Driven
Jiaqi Liu (University of Chicago, CTDS)
Average rating: ****.
(4.33, 3 ratings)
Data-intensive applications, with many layers of transformations and movement from different data sources, can often be challenging to maintain and iterate even after they are initially built and validated. Jiaqi Liu explores how to factor in monitoring, alerting, and tracing data lineage when building data applications that move and transform data across multiple dependencies. Read more.