Presented By
O’Reilly + Cloudera
Make Data Work
March 25-28, 2019
San Francisco, CA
Shriya Arora

Shriya Arora
Senior Data Engineer, Netflix

Shirya Arora works on the data engineering team for personalization at Netflix, which, among other things, delivers recommendations made for each user. The team is responsible for the data that goes into training and scoring of the various machine learning models that power the Netflix home page. They have been working on moving some of the company’s core datasets from being processed in a once-a-day daily batch ETL to being processed in near real time using Apache Flink. Previously, she helped build and architect the new generation of item setup at Walmart Labs, moving from batch processing to stream. They used Storm and Kafka to enable a microservices architecture that allows products to be updated near real time as opposed to once a day on the legacy framework.


4:40pm5:20pm Thursday, March 28, 2019
Sonali Sharma (Netflix), Shriya Arora (Netflix)
Average rating: ***..
(3.00, 2 ratings)
With so much data being generated in real time, what if we could combine all these high-volume data streams and provide near real-time feedback for model training, improving personalization and recommendations and taking the customer experience to a whole new level. Sonali Sharma and Shriya Arora explain how to do exactly that, using Flink's keyed state. Read more.