Hello, if you have realy big data set with various of parameters i would recommend more advanced way - machine learning in e.g. Python. It could help you implement statistical library and AI together.
There are lots of different tools that can be used for statistical analysis, and the best one will depend on what task you're trying to perform.
Microsoft Excel for simple summary statistics and models. Reasonably small data.
R: Programming language that's excellent for statistical models, and data visualisation. Can handle larger data than Excel and useful if you're running multiple, similar analyses. Many packages to extend its functionality. Free and open source.
Python: Programming language with similar capabilities for statistics to R, but a more general programming language and good for machine learning models. Free and open source.
SAS: software that can transform and manage data from different sources and perform statistical analysis on it. Either a point-and-click interface or extended with SAS programming language.
SPSS: software for transforming and analysing data, including statistical analysis. Spreadsheet-like interface, but with many more options than Excel for analysis.
There are others, but this probably covers the most common. Personally, I favour R or Python as its easier to make results reproducible, and easier to generalise repetitive analyses.