With the growing interest in careers in data science and programming for handling data at large scale, it is worth reflecting on ways to be more effective that take us beyond the application of the increasingly sophisticated techniques that are becoming standard for many analysts. Two recent pieces highlight the advantages of strategies for solving problems.
Writing in The Next Web Ari Joury notes the importance of developing an overall approach to problems. He calls attention to five steps: 1) understand the problem, 2) break it down, 3) start with an example, 4) execute, and 5) reflect on possible improvements. These are sensible activities that will lead to greater success no matter what techniques are used.
Presenting a detailed example of a project in Towards Data Science, Holly Emblem highlights the utility of starting analytics projects with some simple heuristics before moving to more complex and sophisticated techniques. The heuristics can be easier to explain to others and they can provide useful benchmarks as a project evolves.
This reminds me of a lesson I learned from my uncle when I was about 8 years old. We were cleaning up some construction debris and came to an area with debris lodged behind some piping. I looked at the situation and said that it would be great if we could get a tool to get behind the piping to remove the debris. My uncle told me that I already had such a tool, and then he reached behind the pipe with his hand and cleaned the area.