Ducks and Data - Sept SF Python at Sentry

Want to learn more about Python and meet other Pythonistas?

Please register: [here](https://ti.to/sfpython/sep-9th-sf-python-sentry?source=meetup) (https://ti.to/sfpython/sep-9th-sf-python-sentry?source=meetup)

Please support our sponsors [Sentry](https://sentry.io/welcome/)!

👉 Submit your 5, 15 or 25 mins talk proposals here: [https://bit.ly/bapyacfp](https://bit.ly/bapyacfp)

SCHEDULED TALKS

Sentry Intro

Generating Realistic Synthetic Data with Python - Saiteja Jonnalagadda Abstract: We all need realistic data to build and test with, but real data often comes with privacy risks and access limits. This talk shows how to generate synthetic data in Python that looks and behaves like the real thing, without exposing anyone's actual information. I will walk through the practical side in Python, from simple statistical approaches to generative models, how to check that the synthetic data is realistic enough to be useful, and how to make sure it does not leak details about the real data it was built from. I have published research on generating synthetic patient records, and I will keep this hands on and approachable, with takeaways you can try in your own projects. Bio: Saiteja Jonnalagadda is a Senior Cloud Engineer at CVS Health who builds AI-driven data systems at large scale. He works on synthetic data, data quality, and machine learning in Python, and he has published research on generative AI for synthetic healthcare data. He is an IEEE member and a peer reviewer for international AI conferences.

Harnessing the Power of Python for Data Analytics - Bev Turnbaugh Abstract: How using Python to ingest data from any source, including public, can fuel your analytics to a new level. MotherDuck introduces Flights, python programs to manipulate data as only python can. https://motherduck.com/docs/concepts/flights/ Bio: I've spent most of my career on the data side — building ETL pipelines, working with databases, and developing data-driven applications for the financial markets. For several years I was part of a team building a fully distributed, in-memory RDBMS, which gave me a deep appreciation for what it takes to make data fast and reliable at scale. More recently I've moved into a customer-facing role, where I get to do the part I've always enjoyed most: working directly with people to solve their toughest data challenges.

AGENDA 6:30p Reconnect with friends! 7:00p Opening remarks, sponsors acknowledgement 7:10p Scheduled talks and Q&A + networking break 8:30p Wrap up last talk, more networking

THIS EVENT IS PRODUCED BY SF Python, a volunteers-run organization aiming to foster the Python Community in the Bay Area