Why do we need to integrate Data mining and Forecasting? 

The most layman and precise understanding of the reasons for the integration of data mining and forecasting is the need for producing an exceptional-quality forecast. The integration approach is one of the most preferred approaches for Data mining and predictive analytics. Why? Because it factually allows access to thousands of independent variables with a potential to process data mining in an effective and efficient manner. These independent variables allow time-series-type data analysis, thus offering more optimized results.

The Take-Away

Along with these three approaches or methods, the business acumen of market experts highly matters in sharpening the forecasts. Various statistical techniques are also applied to develop the final prediction model. This final prediction model is then deployed at the end user level, with the help of appropriate technologies.