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Collaborative Data Science Practices
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Table of contents
1
Introduction
2
Coding Principles
3
Architecture Principles
4
Prototypical R File
5
Prototypical SQL File
6
Prototypical Repository
7
Data at Rest
8
Patterns
9
Security & Private Data
10
Automation & Reproducibility
11
Scaling Up
12
Parallel Collaboration
13
Documentation
14
Style Guide
15
Publishing Results
16
Validation
17
Testing
18
Troubleshooting and Debugging
19
Workstation
20
Considerations when Selecting Tools
21
Growing a Team
22
Material for REDCap Users
23
Material for REDCap Developers
24
Material for REDCap Admins
Appendix
A
Git & GitHub
B
Regular Expressions
C
Snippets
D
Presentations
E
Scratch Pad of Loose Ideas
F
Example Dashboard
G
Example Chapter
H
Acknowledgements
I
References
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11
Scaling Up
11.1
Data Storage
Local File vs Conventional Database vs Redshift
Usage Cases
11.2
Data Processing
R vs SQL
R vs Spark
10
Automation & Reproducibility
12
Parallel Collaboration
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11
Scaling Up
11.1
Data Storage
11.2
Data Processing
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