Great Expectations is a shared, open standard for data quality. It helps data teams eliminate pipeline debt, through data testing, documentation and profiling.

In this beginner-level tutorial on great_expectations, my goal is to help you learn more about great_expectations and find a way to incorporate great_expectations into your own data wrangling or exploratory data analysis as a data testing, data validation, or data documentation tool.

Tutorial level: beginners or starters

Timeline content:
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– (00:00) Video start
– (00:07) Video content introduction
– (02:05) Introducing Code & Jupyter Notebook
– (02:58) great_expectations – what, why and how?
– (05:14) why do you need great_expectations?
– (06:47) What exactly are great_expectations?
– (10:26) great expectations in simple terms
– (13:23) great_expectations as a data documentation tool
– (14:12) Great_expectations method at a glance
– (16:05) installation of awesome_expectations
– (17:11) initialization of great_expectations
– (19:52) context of great_expectations
– (25:27) great_expectations demo with the titanic dataset
– (32:31) Export and apply great_expectations config
– (35:09) Working with time series datasets
– (40:43) Processing SparkDataFrame
– (46:51) expansion great_expectations – debt_expectations
– (49:00) Summary
– (51:34) Credit

Great_expectations GitHub library:
https://github.com/great-expectations/great_expectations

GitHub URL for the examples in the video:
https://github.com/prodramp/publiccode/tree/master/python/greatexpectation-work

Prodramp LLC
https://prodramp.com | @prodramp
https://www.linkedin.com/company/prodramp

Content creator:
Avkash Chauhan (@avkashchauhan)
https://www.linkedin.com/in/avkashchauhan

Tags:
#ai #aicloud #h2oai #driverlessai #machinelearning #cloud #mlops #model #collaboration #deeplearning #modelserving #modeldeployment #keras #tensorflow #pytorch #datarobot #datahub #aiplatform #aicloud #cometml #modelmonitoring #drift #modelregistry #modelmanagement #pandas #pandasprofiling #greatexpectations #great_expectations #datatesting #sparkdataframe #pyspark #assert

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