From the course: Data for Good: Using Data Science in Nonprofits and NGOs
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Problems that can be solved
From the course: Data for Good: Using Data Science in Nonprofits and NGOs
Problems that can be solved
- [Instructor] It starts with defining what the problem is. Now everyone always says that, but what they don't really talk about is how it can be such a moving target. Especially when random events and stakeholders appear. Usually with any data problem, there are lots of moving parts and variables that can be seen and understood, and others that are unknown and almost random. The best place to start is to define what you are looking at as succinctly as possible. It reminds me of a few projects that I've worked on that became more complex, even though I was trying to do some good. One example I can think about is when I was working on a visualization tool for a social support group. And at the end, the software couldn't integrate with the host system. Another example in a similar vein is a volunteer project that I worked on, where all the data was stored in spreadsheets, and there was no way to connect any insights…
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