Maybe you know, in addition to the HydroOffice project, I have also daily job as hydrogeologist at geological survey. In this job I actively use my HydroOffice software package (especially TS Editor). But this toolbox is not applicable for all activities and also is not effective to develop next visual tool with GUI for each problem I solve.
If you work with structured data, stored in different ways (GIS layers, databases, web services, files on disk, etc.), you often face some problem with their transformation, combining, automatic adjustment, statistical processing and visualization. The data treatment and control takes practically about 90% of the time.
For these issues, it is difficult to find an appropriate solution. Solution for me is R language (http://r-project.org). Many know about this awesome tool, but experience tells me that many people still do not know about it.
If you install R on your computer, you can use this scripting language for access your data, process and visualize them. On the one hand, at the beginning this language is not easy to learn, but you master basics, you have access to an incredibly large number of functions and features. If you know to create combined functions in Excel, such as
=IF(AVERAGE(A1:A456)>1;”OK”;”Error”)
then you are able to understand the functions in R language.
R advantage is that you can work well with the data stored in different formats, R is fast, offer very large number of functions, it is possible to create automatically triggered scripts that do all from the loading and processing input data to create final PDF reports that automatically sends via email and the last advantage is that R and its packages are open source.
If you often work with data, I recommend you to learn at least the basics of R. On this blog I occasionally bring some examples of how I used it in my daily work.
In upcoming posts I will introduce my new product that uses R language.
Special note for students:
If you did not end as a hydrogeologist and you know R, you can be employed as a data analyst / scientist, what are now one of the highest paid positions. :-)