Exploratory data analysis should be interpreted carefully. When testing multiple models at once there is a high chance on finding at least one of them to be significant, but this can be due to a type 1 error . It is important to always adjust the significance level when testing multiple models with, for example, a Bonferroni correction . Also, one should not follow up an exploratory analysis with a confirmatory analysis in the same dataset. An exploratory analysis is used to find ideas for a theory, but not to test that theory as well. When a model is found exploratory in a dataset, then following up that analysis with a confirmatory analysis in the same dataset could simply mean that the results of the confirmatory analysis are due to the same type 1 error that resulted in the exploratory model in the first place. The confirmatory analysis therefore will not be more informative than the original exploratory analysis. 
I have used Tableau for developing dashboards and report. It is a very rich visualized dashboard development tool. It is very easy to prepare dashboards. You have the different options and applications in tableau. You can tableau desktop for developing the reports on your desktop. You can also use Tableau server to deploy your dashboards online , so that you can access from any where in the world. It is also providing a free version for public, you can connect to basic data sources like text, csv or excel file. recently they have enhanced data storage limit from 50 MB to 1 GB. so that you can around 1 million records .
Another beauty of tableau is you can connect all types of database.