To generate insights in a predictive analysis framework for support management, raw data is received as input from an in-memory database. A predictive analysis library is integrated in the predictive analysis framework. The predictive analysis framework is generated as a configurable application-programming interface (API). Predictive analysis is performed based on the raw data and the configurable data points. The predictive analysis library functions are invoked from the in-memory database to perform predictive analysis. Predictive data model is generated based on computation performed using a prediction algorithm. Predictive insights are generated based on the predictive data model. The predictive insights are displayed in a user interface associated with a device.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A non-transitory computer-readable medium to store instructions, which when executed by a computer, cause the computer to perform operations comprising: receive raw data from an in-memory database as input in a predictive analysis framework; receive configurable data points as input in the predictive analysis framework; compute predictive analysis for a support management application based on the raw data and the configurable data points; generate predictive data model based on computation performed using a prediction algorithm in the predictive analysis; generate predictive insights in the predictive analysis framework based on the predictive data model; and display the predictive insights at a user interface associated with a device. 2. The computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to: generate the predictive analysis framework as a configurable application programming interface (API); and expose the configurable API as a service. 3. The computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to: receive raw data associated with the support management application and configurable data points associated with incident notes as input in the predictive analysis framework; compute predictive analysis for the support management application based on the raw data and the configurable data points; generate potential notes and incidents as predictive insights based on the predictive analysis; and display the potential notes and incidents as alerts and notifications in the user interface associated with a mobile device. 4. The computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to: generate the predictive data model as OData service; and expose the OData service for consumption by an application. 5. The computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to: integrate a predictive analysis library in the predictive analysis framework; and invoke predictive analysis library functions from the in-memory database while generating predictive data model. 6. The computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to: based on raw data and the configurable data points, compute support, confidence and a lift value; and upon determining that the lift value is greater than a threshold value, generate association rules in the predictive data model. 7. The computer-readable medium of claim 1, further comprises instructions which when executed by the computer further cause the computer to: input the predictive data model to an enterprise application, and generate predictive insights in the predictive analysis framework based on data in the enterprise application. 8. A computer-implemented method of generating insights in a predictive analysis framework for support management, the method comprising: receiving raw data from an in-memory database as input in the predictive analysis framework; receiving configurable data points as input in the predictive analysis framework; computing predictive analysis for a support management application based on the raw data and the configurable data points; generating predictive data model based on computation performed using a prediction algorithm in the predictive analysis; generating predictive insights in the predictive analysis framework based on the predictive data model; and displaying the predictive insights at a user interface associated with a device. 9. The method of claim 8, further comprising: generating the predictive analysis framework as a configurable application programming interface (API); and exposing the configurable API as a service. 10. The method of claim 8, further comprising: receiving raw data associated with support management application and configurable data points associated with incident notes as input in the predictive analysis framework; computing predictive analysis for the support management application based on the raw data and the configurable data points; generating potential notes and incidents as predictive insights based on the predictive analysis; and displaying the potential notes and incidents as alerts and notifications in the user interface associated with a mobile device. 11. The method of claim 8, further comprising: generating the predictive data model as OData service; and exposing the OData service for consumption by an application. 12. The method of claim 8, further comprising: integrating a predictive analysis library in the predictive analysis framework; and invoking predictive analysis library functions from the in-memory database while generating predictive data model. 13. The method of claim 8, further comprising: based on raw data and the configurable data points, computing support, confidence and a lift value; and upon determining that the lift value is greater than a threshold value, generating association rules in the predictive data model. 14. The method of claim 8, further comprising: receiving the predictive data model as input in an enterprise application; and generating predictive insights in the predictive analysis framework based on data in the enterprise application. 15. A computer system for generating insights in a predictive analysis framework for support management, comprising: a computer memory to store program code; and a processor to execute the program code to: receive raw data from an in-memory database as input in the predictive analysis framework; receive configurable data points as input in the predictive analysis framework; compute predictive analysis for a support management application based on the raw data and the configurable data points; generate predictive data model based on computation performed using a prediction algorithm in the predictive analysis; generate predictive insights in the predictive analysis framework based on the predictive data model; and display the predictive insights at a user interface associated with a device. 16. The system of claim 15, wherein the processor further executes the program code to: generate the predictive analysis framework as a configurable application programming interface (API); and expose the configurable API as a service. 17. The system of claim 15, wherein the processor further executes the program code to: receive raw data associated with support management application and configurable data points associated with incident notes as input in the predictive analysis framework; compute predictive analysis for the support management application based on the raw data and the configurable data points; generate potential notes and incidents as predictive insights based on the predictive analysis; and display the potential notes and incidents as alerts and notifications in the user interface associated with a mobile device. 18. The system of claim 15, wherein the processor further executes the program code to: generate the predictive data model as OData service; and expose the OData service for consumption by an application. 19. The system of claim 15, wherein the processor further executes the program code to: integrate a predictive analysis library in the predictive analysis framework; and invoke predictive analysis library functions from the in-memory database while generating predictive data model. 20. The system of claim 15, wherein the processor further executes the program code to: based on raw data and the configurable data points, compute support, confidence and a lift value; and upon determining that the lift value is greater than a threshold value, generate association rules in the predictive data model.