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
How to integrate Great Expecation Data Quality tests in Airflow? | Data pipeline | Data Quality
Lakehouse data validation with Great Expectations in Microsoft Fabric
Always know what to expect from your data with great_expectations
Open-Source Spotlight - Great Expectations (Data Quality Platform) - James Campbell
How to test your Python ETL pipelines | Data pipeline | Pytest
Build an End-to-End ETL Pipeline with Python & PostgreSQL
How to test your Data Pipelines with Great Expectations
Great Expectation Tutorial | Mastering Data Quality
Elevating Data Quality: Great Expectations and Airflow at PepsiCo
Implementing Data Quality in Python w/ Great Expectations
Learn to Efficiently Test ETL Pipelines
Why data engineers should care about data quality (and how to do it right)
36 Row Level Filters in UC | Filter Sensitive Data in Unity Catalog table using Row Level Security
Ex-Google Recruiter Explains Why "Lying" Gets You Hired
How to Use Great Expectations for Data Quality Checks with Airflow
Data Quality Testing in the Medallion Architecture with Pytest and PySpark
How to generate Data Quality Report with Pytest? | Data Quality | Data Quality reports
Learn DBT(databuildtool) in 10 Minutes
Great Expectations (GX) for DATA Testing - Introduction
