Standard Tools/Skills Used in Front Offices
Posted: Fri Nov 16, 2012 9:46 pm
Based on my personal experience:
1) Database server and SQL (most common are SQL Server, MySQL, PostgreSQL)
2) R has gotten very common and is growing rapidly
3) Other programming - this I know the least about, but for us it's R (again), Python, Ruby and some C/C++ (as needed)
If you're working with data from a dozen or more sources you need a database server if you're trying to do serious work. R is no longer really an option for this type of work, even if you use other tools, too. Python and Ruby are the kings for web scraping.
Data modeling (linear regression, mixed models, logistic/multinomial regressions, splines/local regressions), machine learning/classification, graphing/visualization.
Understanding model fit and validation is very important. Back-testing, cross-validation, checking model assumptions.
-Chris
1) Database server and SQL (most common are SQL Server, MySQL, PostgreSQL)
2) R has gotten very common and is growing rapidly
3) Other programming - this I know the least about, but for us it's R (again), Python, Ruby and some C/C++ (as needed)
If you're working with data from a dozen or more sources you need a database server if you're trying to do serious work. R is no longer really an option for this type of work, even if you use other tools, too. Python and Ruby are the kings for web scraping.
Data modeling (linear regression, mixed models, logistic/multinomial regressions, splines/local regressions), machine learning/classification, graphing/visualization.
Understanding model fit and validation is very important. Back-testing, cross-validation, checking model assumptions.
-Chris