data-drift
OpenMetadata
data-drift | OpenMetadata | |
---|---|---|
7 | 26 | |
301 | 4,227 | |
3.0% | 6.8% | |
9.5 | 10.0 | |
3 months ago | 7 days ago | |
HTML | TypeScript | |
GNU General Public License v3.0 only | 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-drift
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Open-Source Observability for the Semantic Layer
Think of Datadrift as a simple & open-source Monte Carlo for the semantic layer era. The repo is at https://github.com/data-drift/data-drift
Datadrift started as an internal tool built at our former company, a large European B2B Fintech. We had data reliability challenges impacting key metrics used for financial and regulatory reporting.
However, when we tried existing data quality tools we where always frustrated. They provide row-level static testing (eg. uniqueness or nullness) which does not address time-varying metrics like revenues. And commercial observability solutions costs $manyK a month and brings compliance and security overhead.
We designed Datadrift to solve these problems. Datadrift works by simply adding a monitor where your metric is computed. It then understands how your metric is computed and on which upstream tables it depends. When an issue occurs, it pinpoints exactly which rows have been updated and introducing the change.
You can also set up alerting and customise it. For example, you can decide to open and assign an Github issue to the analyst owning the revenue metric when a +10% change is detected. We tried to make it easy to customise and developer friendly.
We are thinking of adding features around root cause analysis automation/issues pattern analysis to help data teams improve metrics quality overtime. We’d love to hear your feature requests.
Datadrift is built with Python and Go, and licensed under GPL. Our docs are here: https://github.com/data-drift/data-drift?tab=readme-ov-file#...
Dev set up and demo : https://app.claap.io/sammyt/drift-db-demo-a18-c-ApwBh9kt4p-0...
We’re very eager to get your feedback!
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Would learn Go to contribute to an OS project ? Or should I stick to python ?
I have already started working on it, I started in Go for some part, but I needed python to deploy a Pypi lib. Now its hybrid, and I prefer working with go 😬 but the most rational thinking leads to python.
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Ask HN: Dear startup founders, what have you developed in-house?
We used static testing framework like great expectations but that was not enough. We did not have the budget for the big data observability players like Monte Carlo, so we kept it simple.
Repo if interested: https://github.com/data-drift/data-drift
(Disclaimer: I am focusing full time on this project to see if it's an interesting business opportunity. It's 100% open-source -- feedback welcome!)
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Show HN: Lineage X Snapshot Tooling
https://app.data-drift.io/42527392/Lucasdvrs/dbt-datagit/ove...
You can "technically" install it by yourself, but tbh our focus are on the features, not the adoption. If you are interested it takes roughly 1 hour to configure (choose the data you want to observe, run a python function, install a Github app, add a configuration file), contact us.
The repo: https://github.com/data-drift/data-drift
Roast me
- Non-moving data is a journey
- “Non moving data” is like “Bug free”, it's a lie
OpenMetadata
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How to Dynamically Adjust the Height of a Textarea in ReactJS
In this blog post, I have demonstrated how I addressed the challenge of dynamically adjusting the height of a textarea element based on its content, preventing the need for vertical scrolling in the title section of the OpenMetadata Knowledge article page.
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Blog - Project Nessie: A Look in the Depths
How does this compare with https://github.com/open-metadata/OpenMetadata
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What is your favorite data catalog?
u/cmcau try https://open-metadata.org much easier to setup , for details https://docs.open-metadata.org and for any support https://slack.open-metadata.org
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Data Governance Hands On with Amazon DataZone
Then, a pool of tools appeared on the market with features that allow covering some of the challenges cited, especially those related to data cataloging. Informatica's tool is perhaps the best known among the licensed. Among the open source tools, I highlight Data Hub (www.datahubproject.io) developed on LinkedIn, Open Metadata (https://open-metadata.org/) and Amundsen (https://www.amundsen.io /) powered by Lyft. In addition to cataloging and discovering data artifacts, these tools allow for a view of data lineage, including technical documentation and business terms, and building relationships between data artifacts. Also, it is possible to register data owners, the people responsible for the data in those tools. This greatly facilitates access request and evaluation process (which today is a major bottleneck).
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What OSS are you using for data contracts?
Probably, in order to have it integrate with tools like OpenLineage and OpenMetadata and such I will have to make open-source contributions.
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Thoughts around decube.io (data observability and catalog platform)
We are the team behind OpenMetadata . Our mission is to build a centralized metadata platform that offers data discovery, collaboration, governance and quality. We believe that having tool for each of these categories not only result user frustration but metadata silos.
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Great expectations?
As anyone ever tried open metadata for data QA testing? Curious about that https://open-metadata.org/
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Our data catalog is difficult to manage and not built for the wider org - what can we do?
We're looking to PoC https://open-metadata.org/ shortly
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Looking for an open-source data lineage app, where objects and connections can be manually defined (not just automatically ingested)
Hello everyone, I'm looking for an open-source data lineage app (e.g. tokern, datahubproject, openmetadata).
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Ask HN: Do you use JSON Schema? Help us shape its future stability guarantees
We at OpenMetadata(https://open-metadata.org) use JsonSchema extensively to define the metadata standards. JsonSchema is one of the reasons we are able to ship and get the project to what it is today in quick time. More about it here https://www.youtube.com/watch?v=ZrVTZwmTR3k
What are some alternatives?
lakeFS - lakeFS - Data version control for your data lake | Git for data
datahub - The Metadata Platform for your Data Stack
soda-core - :zap: Data quality testing for the modern data stack (SQL, Spark, and Pandas) https://www.soda.io
marquez - Collect, aggregate, and visualize a data ecosystem's metadata
lightdash - Self-serve BI to 10x your data team ⚡️
odd-platform - First open-source data discovery and observability platform. We make a life for data practitioners easy so you can focus on your business.
tellery - Tellery lets you build metrics using SQL and bring them to your team. As easy as using a document. As powerful as a data modeling tool.
Hyperactive - An optimization and data collection toolbox for convenient and fast prototyping of computationally expensive models.
fullnamematchscore-go - Generates a match score of two person names from 0-100, where 100 is the highest, on how closely two individual full names match. The scoring is based on a series of tests, algorithms, AI, and an ever-growing body of Machine Learning-based generated knowledge
Deeplearning4j - Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.
mask-json-field-transform
Draft.js - A React framework for building text editors.