You probably won't spend as much time to get the data as you will in trying to get it into shape. Raw data is often inconsistent, duplicated, or full of holes. Addresses might be missing, years and dates might be formatted in a thousand different ways, or names might be entered into the wrong fields. You'll have to fix these issues before the data is usable.

This is often an iterative, interactive process. If it's a very large dataset, I might create a sample to work with at this stage. Generally, I start by examining the data files. Once I find a problem, I try to code a solution, which I run on the dataset. After each change, I archive the data, either using a ZIP file or, if the data files are small enough, a version control system. Using a version control system is a good option because I can track the code to transform the data along with the data itself and I can also include comments about what I'm doing. Then, I take a look at the data again, and the entire process starts...