[rluhar]

> 2. Collect examples. Start with a spreadsheet of data that highlights the data you have available.

This is true not just for data science but when trying to solve any numerical problem. Using a spreadsheet (or a R / Python notebook) to implement the algorithm and getting some results has helped me in the past to really understand the problem and avoid dead ends.

For example, when building a FX pricing system, I was able to use a spreadsheet to describe how the pricing algorithm would work and explain it to the traders (the end users). We could tweak the calculations and make sure things were clear to all before implementing and deploying the algorithm.

Great advice!