Automating Large-Scale Data Quality Verification
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data
- Dominant language
- No language data
- Stars
- 17
- Forks
- 5
- PR merge metrics
- No merged PRs in 30d
Description
http://www.vldb.org/pvldb/vol11/p1781-schelter.pdf
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Thanks @EvgenyPetrovsky for sharing
Relates to https://github.com/EvgenyPetrovsky/deeque
Contributor guide
First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
No files, tests, or entry points are named. Start by reading the linked VLDB paper and the related deeque repository, then clarify the intended change and acceptance criteria before coding; the issue currently provides no definition of done.
Written by the indexing model from the issue text.
Assessment
- Domain
- data-engineering, testing-qa
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100