[Live Webinar] The Wonderful World of Data Quality in Python

## Register for webinar here:
https://www.bigmarker.com/neo4j/Data-Umbrella-Webinar

## Time
9am PDT / 12pm EDT / 7pm EAT / 9:30 PM IST

## Talk Level
Intermediate

## Pre-reqs
No skills needed to follow, but some basic level of Python and understanding of/interest in data quality challenges is probably helpful.

## Prep Work
NONE

## Event
In this talk, we’ll give you an overview of the Wonderful World of Data Quality in Python, with a focus on Great Expectations. We’ll first look at the landscape of data quality related open source libraries and look at a few examples such as pydqc, datagristle, bulwark, dvc, dedupe, and others, to give you an idea of the space. In the second half, we will take a closer look at Great Expectations, one of the most popular open source Python packages for data validation and documentation. We’ll demo how to create and run test suites with Great Expectations, and show you how to use the profiling feature to automatically create data tests for you.

## Speaker
Sam Bail is a data professional with a passion for turning high quality data into valuable insights. Sam holds a PhD in Computer Science and has worked for several data-focused startups. In her current role as Engineering Director at Superconductive, she works on “Great Expectations”, an open source Python library for data validation and documentation.

GitHub: https://github.com/spbail
Linkedin: https://www.linkedin.com/in/spbail/
Twitter: https://twitter.com/spbail