How to create Great Epxectations suite? Quality Checks for Data Pipelines | Data Quality скачать в хорошем качестве

How to create Great Epxectations suite? Quality Checks for Data Pipelines | Data Quality

In this video we are going to cover how to create a Great Expecations suite for Data Quality testing. Previously we have created a custom suite as a json file. The Expectation library has built-in functions to carry out the data quality tests. With Great Expectations, you can assert what you expect from the data you load and transform, and catch data issues quickly – Expectations are basically unit tests for your data. Great Expectations also creates data documentation and data quality reports from those Expectations. Link to GitHub repo: https://github.com/hnawaz007/pythonda... Link to previous Great Expecations vidoe :    • How to test your Data Pipelines with Great...   Link to Data Quality playlist:    • How to test your Python ETL pipelines | Da...   Link to Great Expectations Docs: https://docs.greatexpectations.io/docs/ Link to functions glossary: https://great-expectations.readthedoc... #dataquality #Python #greatexpectations 💥Subscribe to our channel:    / haqnawaz   📌 Links ----------------------------------------- #️⃣ Follow me on social media! #️⃣ 🔗 GitHub: https://github.com/hnawaz007 📸 Instagram:   / bi_insights_inc   📝 LinkedIn:   / haq-nawaz   🔗   / hnawaz100   ----------------------------------------- Topics in this video (click to jump around): ================================== 0:00 Introduction Great Expectations 0:38 Notebook & Data Import 1:01 Install and configure Great Expectations 2:10 Create connection to data source 3:45 Create Great Expectations suite 4:37 Define & Run Data QualityTests 7:09 Automated Documentation 8:12 Edit & Update suite