Intelligent data contextualization

1. A method comprising:

receiving a selection of a portion of a first utility visualization, the portion being associated with a subset of utility data;

determining, based at least in part on the selection, a plurality of additional utility visualizations associated with the subset of the utility data;

determining, from among the plurality of additional utility visualizations, one or more previously used utility visualizations;

determining, from among the one or more previously used utility visualizations, one or more candidate utility visualizations that are associated with a type of utility event, wherein the candidate utility visualizations are determined by:

filtering the utility data to locate one or more data elements including one or more measurements, exceptions, or events, relevant with respect to identification of the type of utility event,

comparing the one or more data elements, by a pattern module, to one or more known patterns of measurements, known exceptions, or known events that are associated with the type of utility event;

determining a problem of interest associated with the type of utility event; and

determining, from among the one or more previously used utility visualizations, the one or more candidate utility visualizations that are associated with the problem of interest;

receiving a selection of at least a second utility visualization, from among a ranked list of the one or more candidate utility visualizations; and

outputting information associated with the second utility visualization.

2. The method of claim 1 , wherein the type of utility event comprises one or more of a fraud event, a fault event, or a false positive meter event.

3. The method of claim 1 , wherein the one or more previously used utility visualizations were used by one or more users to view the subset of the utility data or other utility data having a characteristic in common with the subset of the utility data.

4. The method of claim 1 , further comprising:

causing presentation of one or more user comments describing context for previous use of the one or more candidate utility visualizations.

5. The method of claim 1 , further comprising:

ranking the one or more candidate utility visualizations that are associated with the type of utility event.

6. The method of claim 5 , wherein the ranking is based at least in part on user feedback rating the one or more candidate utility visualizations.

7. The method of claim 1 , further comprising:

displaying the ranked list of the one or more candidate utility visualizations.

8. A system, comprising:

one or more processors; and

one or more non-transitory computer-readable media storing computer-executable instructions that, when executed on the one or more processors, cause the one or more processors to perform actions comprising:

receiving a selection of a portion of a first utility visualization, the portion being associated with a subset of utility data;

determining, based at least in part on the selection, a plurality of additional utility visualizations associated with the subset of the utility data;

determining, from among the plurality of additional utility visualizations, one or more previously used utility visualizations;

determining, from among the one or more previously used utility visualizations, one or more candidate utility visualizations that are associated with a type of utility event, wherein the candidate utility visualizations are determined by:

filtering the utility data to locate one or more data elements including one or more measurements, exceptions, or events, relevant with respect to identification of the type of utility event,

comparing the one or more data elements, by a pattern module, to one or more known patterns of measurements, known exceptions, or known events that are associated with the type of utility event;

determining a problem of interest associated with the type of utility event; and

determining, from among the one or more previously used utility visualizations, the one or more candidate utility visualizations that are associated with the problem of interest;

receiving a selection of at least a second utility visualization, from among a ranked list of the one or more candidate utility visualizations; and

outputting information associated with the second utility visualization.

9. The system of claim 8 , the actions further comprising:

causing presentation of one or more user comments describing context for previous use of the one or more candidate utility visualizations.

10. The system of claim 8 , wherein the one or more previously used utility visualizations were used by one or more users to view the subset of the utility data or other utility data having a characteristic in common with the subset of the utility data.

11. The system of claim 8 , wherein the first utility visualization is associated with the type of utility event, the type of utility event comprising one or more of a fraud event, a fault event, or a false positive meter event.

12. The system of claim 8 , the actions further comprising:

ranking the one or more candidate utility visualizations that are associated with the type of utility event.

13. The system of claim 8 , the actions further comprising:

displaying the ranked list of the one or more candidate utility visualizations.

14. A method comprising:

receiving a selection of a portion of a first utility visualization of a type of chart representing utility data, the portion being associated with a subset of the utility data;

determining, based at least in part on the selection, a plurality of additional utility visualizations associated with the subset of the utility data;

determining, from among the plurality of additional utility visualizations, one or more previously used utility visualizations;

determining, from among the one or more previously used utility visualizations, one or more candidate utility visualizations that are associated with a type of utility event, wherein the candidate utility visualizations are determined by:

filtering the utility data to locate one or more data elements including one or more measurements, exceptions, or events, relevant with respect to identification of the type of utility event,

comparing the one or more data elements, by a pattern module, to one or more known patterns of measurements, known exceptions, or known events that are associated with the type of utility event;

determining a problem of interest associated with the type of utility event; and

determining, from among the one or more previously used utility visualizations, the one or more candidate utility visualizations that are associated with the problem of interest;

receiving a selection of at least a second utility visualization, from among a ranked list of the one or more candidate utility visualizations; and

displaying, based at least in part on the selection, the second utility visualization.

15. The method of claim 14 , wherein the type of utility event comprises one or more of a fraud event, a fault event, or a false positive meter event.

16. The method of claim 14 , wherein the one or more previously used utility visualizations were used by one or more users to view the subset of the utility data or other utility data having a characteristic in common with the subset of the utility data.

17. The method of claim 14 , further comprising:

causing presentation of one or more user comments describing context for previous use of the one or more candidate utility visualizations.

18. The method of claim 14 , further comprising:

ranking the one or more candidate utility visualizations that are associated with the type of utility event.

19. The method of claim 18 , wherein the ranking is based at least in part on user feedback rating the one or more candidate utility visualizations.

20. The method of claim 14 , further comprising:

displaying the ranked list of the one or more candidate utility visualizations.