Expense Comp Storage/Database

[Deleted member 126639]

The best, the fastest, is SQLite. It has been around a very long time and is used heavily in industry due to it speed. The language is SQL.

DB Browser for SQLite

sqlitebrowser.org

SQLite Home Page

sqlite.org

Also, this is very easy to use in R, if you do statistics. I typically copy my Excel MLS files over to SQLite and then store the data as SQLite files.

If we're going to go there (this is definitely a time investment) this is a great free/inexpensive option. But the major cloud providers aren't that much more expensive for the kinds of work appraisers do. Excel is very limited for statistical analyses so something like R is the best free option with all others being pretty expensive.

If you're going to be starting from zero knowledge, I'd start with something on Google Could Services or Microsoft Azure so you're learning the newest kind of tech. Azure supports R, and Google probably does as well as Python is such a standard now. But Python is a great way to learn programming (which is the basis for R).

 

[RCA]

If we're going to go there (this is definitely a time investment) this is a great free/inexpensive option. But the major cloud providers aren't that much more expensive for the kinds of work appraisers do. Excel is very limited for statistical analyses so something like R is the best free option with all others being pretty expensive.

If you're going to be starting from zero knowledge, I'd start with something on Google Could Services or Microsoft Azure so you're learning the newest kind of tech. Azure supports R, and Google probably does as well as Python is such a standard now. But Python is a great way to learn programming (which is the basis for R).

R is based mostly on C/C++ language and then Fortran - and of course R itself. Somewhere under 1% of R packages are actually written in Python. However, you can interface R with Python, C#, Haskell, Prolog and many other languages.

Using R is a question of learning high level commands and how to pass parameters to them to get things done. However, Python, C and other more traditional languages require low-level programming - which is good if you want to understand how the various statistical procedures actually work. But for most appraisers or other "applied statisticians", there isn't time to get into low level programming problems.