https://github.com/amcurley/restaurant-data
Science Score: 26.0%
This score indicates how likely this project is to be science-related based on various indicators:
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○CITATION.cff file
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✓codemeta.json file
Found codemeta.json file -
✓.zenodo.json file
Found .zenodo.json file -
○DOI references
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○Academic publication links
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○Academic email domains
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○Institutional organization owner
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○JOSS paper metadata
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○Scientific vocabulary similarity
Low similarity (1.8%) to scientific vocabulary
Last synced: 6 months ago
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JSON representation
Repository
Basic Info
- Host: GitHub
- Owner: amcurley
- Language: Jupyter Notebook
- Default Branch: main
- Size: 132 KB
Statistics
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
- Releases: 0
Created about 5 years ago
· Last pushed about 5 years ago
Metadata Files
Readme
README.md
restaurant-data
Goal:
Create a seamless data experience for the owner and chef of the restaurant
To Do:
- Take data from the s3 bucket from toast.
- Load data into my own s3 bucket or other datalake on aws.
- Format data for tableau.
AWS Pipeline?:
- CloudTrail to trigger step function that runs lambda function that connects S3 Buckets. S3 Kinesis data firehose to Amazon Quicksight.
Owner
- Login: amcurley
- Kind: user
- Repositories: 1
- Profile: https://github.com/amcurley