Mobile wireless customer micro-care apparatus and method

1. A method, comprising:

receiving, by a system comprising a processor, a signal corresponding to a customer associated with a user equipment that is a member of a defined population of user equipment;

retrieving, by the system, a data package comprising metrics collected by the user equipment, wherein the metrics concern performance of the user equipment via a network;

storing, by the system, the data package in a first memory location of random access memory locations in a memory device of the system;

allocating, by the system to a customer care process, a group of processor nodes from a distributed pool of processor nodes;

executing, by the system, the customer care process using the random access memory locations and the group of processor nodes, comprising:

transforming, by a first processor node of the group of processor nodes, the metrics in the first memory location into measures that are configured to enable derivation of a key performance indicators concerning the performance of the user equipment;

outputting, by the first processor node, the measures to a second memory location of the random access memory locations;

generating, by a second processor node of the group of processor nodes, an enriched measure by processing the measures in the second memory location based on correlations of user equipment events in a time sequence;

outputting, by the second processor node, the enriched measure to a third memory location of the random access memory locations;

transforming, by a third processor node of the group of processor nodes, the enriched measure in the third memory location into a first key performance indicator that is specific to the performance of the user equipment;

outputting, by the third processor node, the first key performance indicator to a fourth memory location of the random access memory locations;

comparing, by a fourth processor node of the group of processor nodes, the first key performance indicator of the user equipment in the fourth memory location to a second key performance indicator of the defined population of user equipment;

outputting, by the fourth processor node, a result of the comparison of the first key performance indicator to the second key performance indicator to a fifth memory location of the random access memory locations;

using, by a fifth processor node of the group of processor nodes, the result of the comparison in the fifth memory location to identify a resolution to a problem with an operation of the user equipment; and

outputting, by the fifth processor node, the resolution to a sixth memory location of the random access memory locations.

2. The method of claim 1 , wherein executing the customer care process is performed without writing contents of the first memory location, the second memory location, the third memory location, the fourth memory location, the fifth memory location, and the sixth memory location to a disk storage of the system.

3. The method of claim 1 , wherein the result of the comparison comprises a variance between the first key performance indicator of the user equipment and the second key performance indicator of the defined population of user equipment.

4. The method of claim 1 , further comprising storing, by the system, data packages corresponding to additional customers that are associated with respective user equipment of a subset of the defined population of user equipment, and wherein a record is kept that enables retrieval, during a predetermined range of time, of a specified data package associated with any specified user equipment of the respective user equipment.

5. The method of claim 1 , wherein resolving the problem with the operation of the user equipment comprises at least one of installing an update on the user equipment or adjusting a setting of the user equipment.

6. The method of claim 1 , wherein the method is performed on-demand via a device associated with the customer.

7. The method of claim 1 , wherein transforming the metrics into the measures comprises anonymizing the metrics.

8. The method of claim 1 , wherein the user equipment of the defined population of user equipment are associated with respective customers that are similar.

9. The method of claim 1 , wherein the resolution is applied to another user equipment of the defined population of user equipment.

10. A non-transitory machine-readable medium, comprising executable instructions that, when executed by a processor of a system, facilitate performance of operations, comprising:

receiving a signal corresponding to a customer associated with a user equipment that is a member of a defined population of user equipment;

obtaining a data package comprising metrics collected by the user equipment, wherein the metrics concern performance of the user equipment in a network;

storing the data package in a first memory location of random access memory locations in a memory device of the system;

allocating, to a customer care process, a group of processor nodes from a distributed pool of processor nodes;

executing the customer care process using the random access memory locations and the group of processor nodes, comprising:

transforming, by a first processor node of the group of processor nodes, the metrics in the first memory location into measures that are configured to enable derivation of a key performance indicators concerning the performance of the user equipment, and outputting, by the first processor node, the measures to a second memory location of the random access memory locations;

generating, by a second processor node of the group of processor nodes, an enriched measure by processing the measures in the second memory location based on correlations of user equipment events in a time sequence, and outputting, by the second processor node, the enriched measure to a third memory location of the random access memory locations;

transforming, by a third processor node of the group of processor nodes, the enriched measure in the third memory location into a first key performance indicator that is specific to the performance of the user equipment, and outputting, by the third processor node, the first key performance indicator to a fourth memory location of the random access memory locations;

comparing, by a fourth processor node of the group of processor nodes, the first key performance indicator of the user equipment in the fourth memory location to a second key performance indicator of the defined population of user equipment, and outputting, by the fourth processor node, a result of the comparison of the first key performance indicator to the second key performance indicator to a fifth memory location of the random access memory locations; and

using, by a fifth processor node of the group of processor nodes, the result of the comparison in the fifth memory location to identify a resolution to a problem with an operation of the user equipment, and outputting, by the fourth fifth processor node, the resolution to a sixth memory location of the random access memory locations.

11. The non-transitory machine-readable medium of claim 10 , wherein executing the problem resolution process is performed without writing contents of the first memory location, the second memory location, the third memory location, the fourth memory location, the fifth memory location, and the sixth memory location to a disk storage of the system.

12. The non-transitory machine-readable medium of claim 10 , wherein the result of the comparison comprises a variance between the first key performance indicator of the user equipment and the second key performance indicator of the defined population of user equipment.

13. The non-transitory machine-readable medium of claim 10 , wherein the operations further comprise storing data packages from additional customers that are associated with respective user equipment of a subset of the defined population of user equipment, and wherein a record is kept that enables retrieval, during a predetermined range of time, of a data package associated with any specific user equipment of the respective user equipment.

14. The non-transitory machine-readable medium of claim 10 , wherein resolving the problem with the operation of the user equipment comprises at least one of installing an update on the user equipment or adjusting a setting of the user equipment.

15. The non-transitory machine-readable medium of claim 10 , wherein the operations are performed on-demand based on a request received from the customer.

16. The non-transitory machine-readable medium of claim 10 , wherein transforming the metrics into the measures comprises anonymizing the metrics.

17. A system, comprising:

a processor; and

a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising:

receiving a signal corresponding to a customer associated with a user equipment that is a member of a defined population of user equipment;

obtaining a data package comprising metrics collected by the user equipment, wherein the metrics concern performance of the user equipment;

storing the data package in a first memory location of random access memory locations in the memory of the system;

allocating, to a customer care process, a group of processor nodes from a distributed pool of processor nodes;

executing the customer care process using the random access memory locations and the group of processor nodes, comprising:

transforming, by a first processor node of the group of processor nodes, the metrics in the first memory location into measures that are configured to enable derivation of key performance indicators concerning the performance of the user equipment, and outputting, by the first processor node, the measures to a second memory location of the random access memory locations;

generating, by a second processor node of the group of processor nodes, an enriched measure by processing the measures in the second memory location based on correlations of user equipment events in a time sequence, and outputting, by the second processor node, the enriched measure to a third memory location of the random access memory locations;

transforming, by a third processor node of the group of processor nodes, the enriched measure in the third memory location into a first key performance indicator that is specific to the performance of the user equipment, and outputting, by the third processor node, the first key performance indicator to a fourth memory location of the random access memory locations;

comparing, by a fourth processor node of the group of processor nodes, the first key performance indicator of the user equipment in the fourth memory location to a second key performance indicator of the defined population of user equipment, and outputting, by the fourth processor node, a result of the comparison of the first key performance indicator to the second key performance indicator to a fifth memory location of the random access memory locations; and

using, by a fifth processor node of the group of processor nodes, the result of the comparison in the fifth memory location to identify a resolution to a problem with an operation of the user equipment, and outputting, by the fifth processor node, the resolution to a sixth memory location of the random access memory locations.

18. The system of claim 17 , wherein the defined population of user equipment is associated with respective customers that are similar, and wherein the resolution is applied to another user equipment of the defined population of user equipment other than the user equipment.

19. The system of claim 17 , wherein executing the customer care process is performed without writing contents of the first memory location, the second memory location, the third memory location, the fourth memory location, the fifth memory location, and the sixth memory location to a disk storage of the system.

20. The system of claim 17 , wherein the result of the comparison comprises a variance between the first key performance indicator and the second key performance indicator.