elementary
re_data
elementary | re_data | |
---|---|---|
30 | 15 | |
1,740 | 1,525 | |
1.8% | 0.4% | |
9.8 | 6.6 | |
6 days ago | 8 days ago | |
HTML | HTML | |
Apache License 2.0 | GNU General Public License v3.0 or later |
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.
elementary
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Open source data observability tools with UI?
Check out https://github.com/elementary-data/elementary
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Data Validation tools
In this case, do https://github.com/elementary-data/elementary or https://greatexpectations.io help?
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SQL “Visualization” Website/Resource?
That makes explain little easier to read. No graph though. Also https://github.com/elementary-data/elementary should know howto draw pretty graphs for data lineage ( ie. what columns comes where and is used how)
- Open source dbt tests monitoring
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Suggestions for open source anomaly-detection, linting and metadata solutions?
there is elementary lineage / elementary-data which seems to be good try to solve those problem, i havent tested it well https://github.com/elementary-data/elementary
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Snowflake SQL AST parser?
Some things you might be interested in are re_data and Elementary Data.
- Launch HN: Elementary (YC W22) – Open-source data observability
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Data lineage info to a table in the DWH
Hi all, As part of building Elementary (open source data reliability), we implemented support of a new Snowflake feature (write operations in the access_history view). The change they made is most useful for understanding data lineage, which we solve (among other use cases :)).
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Launch HN: Metaplane (YC W20) – Datadog for Data
I recently stumbled on an open-source tool with a similar premise: https://github.com/elementary-data/elementary-lineage
you can check it out
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Lightweight data profiling tools / relationship discovery
Hi! we are working on an open source data lineage solution that might be helpful for your use case to learn the relationship between tables, we don't support column level just yet but we are working on it. Please let me know if we can help somehow and feel free to check it out here - https://github.com/elementary-data/elementary-lineage
re_data
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How to design a software for extracting and validating data in existing DB(s)
There’s also this open source tool I think is doing kind of what the OP is looking for, re_data. The source code lives here: https://github.com/re-data/re-data
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What are the 5 hottest dbt Repositories one should star on GitHub 2022?
What are the 5 hottest dbt Repositories one should star on Github 2022?
dbt is a software framework that sits in the middle of the ELT process. It represents the transformative layer after loading data from an original source. Dbt combines SQL with software engineering principles.
Here are my top5!
- Lightdash (https://github.com/lightdash/lightdash): Lightdash converts dbt models and makes it possible to define and easily visualize additional metrics via a visual interface.
- ⏎ re_data (https://github.com/re-data/re-data): Re-Data is an abstraction layer that helps users monitor dbt projects and their underlying data. For example, you get alerts when a test failed or a data anomaly occurs in a dbt project.
- evidence (https://github.com/evidence-dev/evidence): Evidence is another tool for lightweight BI reporting. With Evidence, you can build simple reports in "medium style" using SQL queries and Markdown.
- Kuwala (https://github.com/kuwala-io/kuwala): With Kuwala, a BI analyst can intuitively build advanced data workflows using a drag-drop interface on top of the modern data stack without coding. Behind the Scenes, the dbt models are generated so that a more experienced engineer can customize the pipelines at any time.
- fal ai (https://github.com/fal-ai/fal): Fal helps to run Python scripts directly from the dbt project. For example, you can load dbt models directly into the Python context which helps to apply Data Science libraries like SKlearn and Prophet in the dbt models.
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What are the hottest dbt Repositories you should star on Github 2022? - Here are mine.
re_data ( https://github.com/re-data/re-data ) Re_data is an abstraction layer that helps users monitor dbt projects and their underlying data. For example, you get alerts when a test failed or a data anomaly occurs in a dbt project and which underlying metric is affected. In addition, the lineage graph is also intuitively displayed. Re-data is one of two others frameworks focusing on the observability aspect of lengthy pipelines in dbt (check also out: open-metadata and Elementary).
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What are your hottest dbt repositories in 2022 so far? Here are mine!
- ⏎ re_data: Re-Data is an abstraction layer that helps users monitor dbt projects and their underlying data. For example, you get alerts when a test failed or a data anomaly occurs in a dbt project.
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Snowflake SQL AST parser?
Some things you might be interested in are re_data and Elementary Data.
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Sentry for Data Teams
Around a year ago I launched re_data (an open-source data reliability tool) here. After some pivots, we seem to be getting traction and this is how it looks now: https://www.getre.io/. Super interested in getting your feedback and suggestions on the direction :)
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Launch HN: Elementary (YC W22) – Open-source data observability
Nice project, at re_data we just got over a lot of your new updates and it seems a quite large part of your project is "inspired" by code from our library https://github.com/re-data/re-data. Even with parts, we are not especially proud of ;)
If you decide to copy not only ideas but a big part of internal implementation, I think you should include that information in your LICENSE.
Cheers
- How are you guys testing your data?
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great_expectations VS redata - a user suggested alternative
2 projects | 24 Sep 2021
It's more convenient when you are already using dbt and don't want to set up a separate workflow for testing data when it can be done with dbt inside the data warehouse. Also the thing re_data does well is letting you create time-based metrics about your data quality instead of just tests (a lot of the tests can be rewritten to that) That allows you to do a couple of things more than GE, you can for example easily visualize or look for anomalies in those. You can also compute tests much more efficiently. Research about computing metrics as a good way of doing data quality was actually done by the team behind deequ: http://www.vldb.org/pvldb/vol11/p1781-schelter.pdf I'm the author, so obviously I'm a bit biased :)
- re_data - open-source data quality library build on top of dbt.
What are some alternatives?
sqllineage - SQL Lineage Analysis Tool powered by Python
great_expectations - Always know what to expect from your data.
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.
tiddlywiki-docker - Tools for running TiddlyWiki via a Docker container
lightdash - Self-serve BI to 10x your data team ⚡️
soda-sql - Data profiling, testing, and monitoring for SQL accessible data.
dbt-core - dbt enables data analysts and engineers to transform their data using the same practices that software engineers use to build applications.
gradio - Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!
deequ - Deequ is a library built on top of Apache Spark for defining "unit tests for data", which measure data quality in large datasets.