data-caterer
soda-core
| data-caterer | soda-core | |
|---|---|---|
| 3 | 5 | |
| 14 | 1,768 | |
| - | 2.5% | |
| 8.9 | 8.9 | |
| 16 days ago | 2 days ago | |
| Scala | Python | |
| Apache License 2.0 | Apache License 2.0 |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
data-caterer
soda-core
- Looking for Unit Testing framework in Database Migration Process
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Data profiling tools / approaches?
Tools like Soda Core could be really helpful for this. For example, it allows you to set up a change over time threshold which could take the form of: change avg last 3 for missing_count(column_name) < 20%
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Data QC? Great Expectations?
You can give https://github.com/sodadata/soda-core - open source and (in my opinion) easy to get a lot of value with minimum effort.
- Show HN: Soda Core is now GA – Test data like you would test your code
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Soda Core (OSS) is now GA! So, why should you add checks to your data pipelines?
Give Soda Core a try! It's really easy. If you only have 2 minutes, check out our docs or interactive demo (pretty cool no?). If you have a bit more time, install it and give it a spin! Want to look at it later? Star on Github. Got stuck? As in our Slack community.
What are some alternatives?
data-validator - A tool to validate data, built around Apache Spark.
great_expectations - Always know what to expect from your data.
arch-go - Architecture checks for Go projects
dbt-data-reliability - dbt package that is part of Elementary, the dbt-native data observability solution for data & analytics engineers. Monitor your data pipelines in minutes. Available as self-hosted or cloud service with premium features.
soda-spark - Soda Spark is a PySpark library that helps you with testing your data in Spark Dataframes
dictum - Describe business metrics with YAML, query and visualize in Jupyter with zero SQL
cuallee - Possibly the fastest DataFrame-agnostic quality check library in town.
data-diff - Compare tables within or across databases
dbt-snowflake-monitoring - A dbt package from SELECT to help you monitor Snowflake performance and costs
pointblank - Data quality assessment and metadata reporting for data frames and database tables
ydata-profiling - 1 Line of code data quality profiling & exploratory data analysis for Pandas and Spark DataFrames.