Data Scientist in 10 steps

1. You know quantitative data analysis methods and techniques.
2. You can design data model.
3. You know data querying languages.
4. You know business domain of data you are analyzing.
5. You like to spend hours, days, weeks trying to make sense of data.
6. You like to run analytical models using proprietary and off the shelf tools and then spend hours, days, weeks trying to make sense of data.
7. You know your stuff around Massively Parallel Processing Systems.
8. You know your stuff around ETL.

Interpreted Languages in 10 Steps

1. Interpreted programming languages are languages which rely on another program (interpreter) to interpret code written by a programmer, into machine specific language.
2. Interpreted programming languages' objective is to provide development platform neutrality and shield programmers from specifics of the underlying operating system. History has proven that Operating System transparency is someone theoretical as nuances in interpreters' implementations and API, quite often prove migration projects to be as easy as fitting an elephant into a shoe box.