A system and method for providing a prediction is disclosed. A series of historical data or profiles are collected and stored on a database. Using software to provide a first set of predictive patterns from the historical profiles and a second set of predictive patters from the first set of predictive patterns from which the prediction for a particular subject such as sales can be provided.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A non-transient computer readable medium containing program instructions for causing a computer to perform the method of: collecting a first historical profile for a desired subject; creating a forecast for the desired subject based on the first historical profile; creating a first set of predictive patterns based on the created forecast; discarding the first historical profile once the first set of predictive patterns for the desired subject are created; receiving a request for a prediction of the desired subject; and creating a second set of predictive patterns for the desired subject based on the first set of predictive patterns to create the prediction. 2. The non-transient computer readable medium of claim 1, wherein creating the first set of predictive patterns is also based on an updated first historical profile. 3. The non-transient computer readable medium of claim 1 further comprising: saving the first and second sets of predictive patterns to a predictive patterns repository; and displaying the requested prediction on a display. 4. The non-transient computer readable medium of claim 1, wherein the prediction desired subject includes sales, cash flow, potential customer claims, fees associated with third-party services, warranty, returns, energy, and supplies. 5. The non-transient computer readable medium of claim 1, wherein the prediction desired subject is categorize by date, hour, item, department, store, or division. 6. The non-transient computer readable medium of claim 1, wherein a second historical profile is within a statistical 5% difference from the first historical profile and the first and second historical profiles are dynamically updatable. 7. The non-transient computer readable medium of claim 1, wherein if the first and second historical profiles are similar within 95%, then information of one of the historical profiles will be assimilated into the other historical profile and then deleted. 8. The non-transient computer readable medium of claim 1, wherein the step of creating g the first set of predictive patterns takes more time than the step of creating the second set of predictive patterns. 9. The non-transient computer readable medium of claim 1, wherein the first and second set of predictive patterns are stored vertically in a memory of a computing device. 10. A method of forecasting of a desired subject, comprising the steps of: collecting a first historical profile for the desired subject from a database stored on a computing device; creating, with a processor of the computing device, a forecast for the desired subject based on the first historical profile; creating, with the processor of the computing device, a first set of predictive patterns based on the created forecast; discarding the first historical profile from the database once the first set of predictive patterns for the desired subject are created; receiving a request for a prediction of the desired subject; and creating, with the processor of the computing device, a second set of predictive patterns for the desired subject based on the first set of predictive patterns to create the prediction and an updated first historical profile. 11. The method of claim 10, wherein the step of creating the first set of predictive patterns is also based on a second historical profile. 12. The method of claim 11, wherein for the first historical profile is a time of sale of an item and the second historical profile is what the item is. 13. The method of claim 10, further comprising the steps of: saving the first and second sets of predictive patterns to a predictive patterns repository on a memory of the computing device; and displaying the requested prediction on a display. 14. The method of claim 10, wherein the prediction desired subject includes sales, cash flow, potential customer claims, fees associated with third-party services, warranty, returns, energy, and supplies. 15. The method of claim 10, wherein the prediction desired subject s categorize by date, hour, item, department, store, or division. 16. The method of claim 10, wherein a second profile is within a statistical 5% difference from the first historical profile and the first and second historical profiles are dynamically updatable. 17. The method of claim 10, wherein if the first and second historical profiles are similar within 95%, then information of one of the historical profiles will be assimilated into the other historical profile and then deleted. 18. The method of claim 10, wherein the step of creating the first set of predictive patterns takes more time than the step of creating the second set of predictive patterns. 19. The method of claim 10, wherein the first and second set of predictive patterns are stored vertically in a memory of a computing device. 20. A computing device that provides a prediction, comprising: a processor in communication with a memory; and a database having a first historical profile for a desired subject and being stored on the memory, wherein the processor performs the following steps: creating a forecast for the desired subject based on the first historical profile; creating a first set of predictive patterns based on the created forecast; discarding the first historical profile from the database once the first set of predictive patterns for the desired subject are created; receiving a request for a prediction of the desired subject; and creating, with the processor of the computing device, a second set of predictive patterns for the desired subject based on the first set of predictive patterns to create the prediction and an updated first historical profile.