Join us as Ian Eaves, Data Scientist of Bellhops, shares how he uses user-defined functions (UDFs), Amazon Redshift, and Chartio to save multiple hours each week by running Python analysis directly in Amazon Redshift.
Bellhops, one of the fastest growing moving services platform in the US, serves over 80+ markets and is constantly monitoring large volumes of incoming data around their movers, users, and interactions within the site.
However, their system of exporting data to use Python on their local machine to run analysis wasn't efficient nor scalable.
Bellhops needed a faster way to analyze their data in real time.
Learn how Bellhops uses Amazon Redshift and Python UDFs to avoid inefficient data extraction as well as parallelize and share statistical analyses directly within Chartio.
Bellhops will be discussing best practices and how this trio opens up new possibilities for data science teams working with large data sets.
Duration: 45 minutes
Start: 11:00 am PST / 2:00pm EST
Data Scientist at Bellhops; M.S. Physics; Background in computational modeling (esp. of quantum systems); Worked at the Helmholtz Institute (Berlin, GER)
AJ Welch is a Data Engineer at Chartio. AJ is an expert in helping clients build data warehousing and BI solutions to improve their analytic capabilities.
Brandon Chavis is a Solutions Architect on the Amazon Partner team. He is based in Seattle, Wa, and has been with AWS for over three years. He focuses on helping customers build high-scale and low-cost architectures in the cloud.