Methods and systems for using multiple data sets to analyze performance metrics of targeted companies

A data analysis system, comprising:

• a processor in electronic communication with a plurality of disparate, non-fundamental data sources, each of the data sources providing electronically accessible, measurable data that is different from any of the other ones of the plurality of disparate, non-fundamental data sources;
• and
• a database connected with said processor;
• said processor configured to:
• receive an input performance metric for a selected company;
• collect sets of data related to said performance metric from each of said plurality of disparate, non-fundamental data sources;
• validate said sets of data;
• discard invalid sets of data from said collected data sets;
• combine the non-discarded sets of data into a combined data set;
• store said combined data set in said database;
• select an analytical process to apply to the stored combined data set, said analytical process being selected from a group consisting of regression analysis, time series analysis, smoothing methods, spectral analysis, neural networks, artificial intelligence, and machine learning;
• apply the selected analytical process to the combined data set to create a model of the performance metric;
• validate the model of the performance metric against the actual performance of the selected company;
• and
• if model is not validated, correct said model.