108 Data Analysis
108.40.05 Data Analysis - Tools should be generically useful

Tools should be generically useful

Because of the fact that every project is different, any tool (or data schema) that is purpose-built is going to fall short of what needs to be done during an actual analysis. There will be an edge case - every time. We need to be more about flexible process than focused on purpose-built tooling.

There were always problems when doing analysis. Often it was tool related. Custom built, in-house tools would often fail when we tried to use it on a project. (Lucky8 Daily Q2 2017, 20170328)

The primary causes of problems which having better tools would solve:
- LACK OF WORKING TOOLS: Tools would simply fail due to bugs
- LACK OF TOOLING: Tools would not work because of use cases we didn't consider or didn't support
- LACK OF TOOLING: The Level Set tooling was not robust enough so it had to be done manually
- LACK OF SHARED PLATFORM: People were more comfortable working in MS products, so real-time collaboration was always a problem
- LACK OF PROCESS: The deliverable was different every time

And follow 108.40.30 Data Analysis - Tools and environment best practices

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