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BABlessing Angusdata-with-naza.hashnode.dev9h ago · 9 min read

Data Tests, Quality Checks, and Observability: The Three Layers Every Pipeline Needs

In Part 1 of this series, I defined data quality and walked through the six dimensions that the industry uses to measure it. If you have not read that piece, I would start there because the framework

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ASAnuj Syalanujsyal.comDec 8, 2024 · 7 min read

Mastering Data Quality in ETL Pipelines with Great Expectations

In the world of data engineering, ensuring data quality is paramount. From business analysts relying on dashboards to C-level executives making strategic decisions, and data scientists training machine learning models — everyone depends on the qualit...

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IOIlham Oulakbirensuringdataqualityandgovernance.hashnode.devSep 23, 2024 · 4 min read

Best Practices for Data Engineers: Ensuring Data Quality and Governance

Introduction: In the world of data engineering, ensuring the quality and governance of data is as important as building robust pipelines and scalable architectures. Without proper governance and quality measures, the data you work with can lead to in...

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MNMutabazi Nobleairqoengineering.hashnode.devDec 12, 2022 · 11 min read

Data Unit Testing With Great Expectations and Cloud Functions

At AirQo, we collect large amounts of data every day from our low-cost monitors deployed throughout the African continent, with the majority being in Uganda, as well as data from our partners such as Kampala Capital City Authority that are streamed e...

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IBItay Braunpostgres.hashnode.devDec 3, 2022 · 6 min read

Preventing Data Quality problems from hitting the Production environment using Great Expectations

By Itay Braun, CTO, Metis In this post you'll learn how to apply data quality tests using an open-source platform called Great Expectations. Why Should I care? Data quality is important because it determines the accuracy and reliability of the inform...

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DDataChefblog.datachef.coApr 28, 2022 · 6 min read

How to Use S3 for Storing Great Expectation Results

Introduction Great Expectations(GE) allows us to oversee data pipelines and helps us to create data quality checks. In our previous post on running GE on EMR, we explored how to set up GE for your data pipeline and validate your data sources. Recentl...

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DDataChefblog.datachef.coJan 28, 2021 · 8 min read

How to run Great Expectations on EMR

What is Great Expectations Great Expectations is a great tool to validate the quality of your data and can be configured against a number of data sources, including BigQuery, MySQL, Snowflake and Athena. It helps you to test data instead of code. Let...

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#great-expectations

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Trending tags this week

Data Tests, Quality Checks, and Observability: The Three Layers Every Pipeline Needs

Mastering Data Quality in ETL Pipelines with Great Expectations

Best Practices for Data Engineers: Ensuring Data Quality and Governance

Data Unit Testing With Great Expectations and Cloud Functions

Preventing Data Quality problems from hitting the Production environment using Great Expectations

How to Use S3 for Storing Great Expectation Results

How to run Great Expectations on EMR