6. The method of claim 5 wherein the transformations are synchronized in a serial and parallel manner for each data value, the transformations selected from the group consisting of transformations performing a unique and predefined task of transforming the input data to generate a different form of data named as output data; transformations performing validating the output values of other transformations for the values compliant to various business related logic or relationship between the data values; transformations performing their predefined tasks in a synchronized manner have an ability to transform the input document to a final deliverable data value; transformations for splitting a data value to deliver two or more different output data values; and transformations for merging multiple outputs of other transformations to derive a single output data value, such that each step of transformation, in the process of transforming the input data to output data, generates a component confidence.
6. The method of claim 5 wherein the transformations are synchronized in a serial and parallel manner for each data value, the transformations selected from the group consisting of transformations performing a unique and predefined task of transforming the input data to generate a different form of data named as output data; transformations performing validating the output values of other transformations for the values compliant to various business related logic or relationship between the data values; transformations performing their predefined tasks in a synchronized manner have an ability to transform the input document to a final deliverable data value; transformations for splitting a data value to deliver two or more different output data values; and transformations for merging multiple outputs of other transformations to derive a single output data value, such that each step of transformation, in the process of transforming the input data to output data, generates a component confidence. 11. The method of claim 6 wherein computing the final confidence from the statistically significant and favorably impacting component confidences, associated weights and the non-linear statistical model, in a production mode, further comprises employing an automated data extraction mechanism to deliver data value and final confidence by: using the series of transformations on a batch of production input data streams to compute systematically the output data value; deriving, from each of the transformations, the component confidence; combining the statistically significant component confidences with the corresponding associated weights; and using both the selected component confidences and the associated weights in the non-linear statistical model to determine a final confidence.