dbt-data-reliability
soda-core
Our great sponsors
| dbt-data-reliability | soda-core | |
|---|---|---|
| 2 | 5 | |
| 338 | 1,751 | |
| 4.7% | 3.8% | |
| 9.7 | 9.0 | |
| 6 days ago | 1 day ago | |
| Python | 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.
dbt-data-reliability
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How to store dbt run and test results in tables + code example
The entire implementation is available in our open source dbt package.
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Launch HN: Elementary (YC W22) – Open-source data observability
For any dbt users, their reliability package has the best and most comprehensive way to upload artifacts directly to the warehouse after a dbt invocation.
https://github.com/elementary-data/dbt-data-reliability
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?
deequ - Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.
great_expectations - Always know what to expect from your data.
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.
dictum - Describe business metrics with YAML, query and visualize in Jupyter with zero SQL
re_data - re_data - fix data issues before your users & CEO would discover them 😊
cuallee - Possibly the fastest DataFrame-agnostic quality check library in town.
sqllineage - SQL Lineage Analysis Tool powered by Python
data-diff - Compare tables within or across databases
versatile-data-kit - One framework to develop, deploy and operate data workflows with Python and SQL.
dbt-snowflake-monitoring - A dbt package from SELECT to help you monitor Snowflake performance and costs
dbt-documentor - ✍️ dbt doc generator for advanced data teams
pointblank - Data quality assessment and metadata reporting for data frames and database tables