Agile Data Science on Greenplum [using Airflow]
Aditya Padhye works professionally as a Data Engineer for Pivotal Software, based in San Francisco, California. He has earned a Bachelor's degree in Computer Engineering from COEP and a Master's in Information Systems from Carnegie Mellon University. Find him on LinkedIn
Ambarish Joshi is a data scientist at Pivotal, with a background in software engineering, statistics and machine learning. Previously, he worked at an education startup where he led the analysis of student performance including predicting the end of the year scores, classifying high-risk students and identifying anomalous student behaviour to help educators effectively intervene struggling students. He worked with Carnegie Mellon researchers to perform controlled experiments to analyze student behaviour. He has recently worked on a variety of use-cases focusing on Geospatial data, Log Analysis, Voice Recognition and Deep Learning. He has a passion for operationalization of data science models to build smart apps and holds an M.S. in Information Systems from Carnegie Mellon University.
In this demo, we’ll see how to use Airflow to build and manage Data Science workflows in Greenplum. We'll also take a look at how we can quickly iterate on, and continuously improve, data science models that have been deployed.
Technologies used: - Greenplum - Airflow
- 2019 March 20 15:00 EDT
- 50 min
- Riverside Suite
- Postgres Conference