Assisted analytics

1. A system comprising:

at least one processor; and

a memory device storing an application that adapts the at least one processor to:

compute an outlier boundary for a dimension data value by applying statistical analysis to at least a portion of data organized under the dimension data value as assisted analytics time frame data sets;

detect at least one outlier in the assisted analytics time frame data sets that is outside of the dimension data value outlier boundary;

produce a dimension data value outlier factor based on a weighting associated with an assisted analytics time frame for each of the at least one outlier;

generate one or more dimension outlier factors based at least in part on the dimension data value outlier factor derived from the detected at least one outlier; and

map the one or more dimension outlier factors to a corresponding dimension impact rating value, the mapping structured to facilitate user-controllable visualization in an electronic interface of an impact of each of a set of dimensions of the data organized under the dimension data value for a portion of the assisted analytics time frame data sets.

2. The system of claim 1 , wherein the weighting is based on one or more of a recency of the time frame, a business cycle, or an importance of the dimension data value to a focus of business performance.

3. The system of claim 1 , wherein the application further adapts the at least one processor to apply the statistical analysis to at least a portion of the data organized under the dimension data value by calculating a standard deviation of data entries organized by the dimension data value.

4. The system of claim 3 , wherein the dimension data value outlier boundary is computed via application of a multiple of the standard deviation.

5. The system of claim 1 , wherein the application further adapts the at least one processor to apply the statistical analysis to at least a portion of the data organized under the dimension data value by dynamically determining the statistical analysis.

6. The system of claim 1 , wherein the application further adapts the at least one processor to dynamically determine the statistical analysis based on at least one of a size of a data structure for the assisted analytics time frame data sets, a user preference, a previously used statistical analysis, or a user ranking of the statistical analysis.

7. The system of claim 1 , wherein the application further adapts the at least one processor to dynamically determine the statistical analysis based at least in part on a count of outliers.

8. The system of claim 1 , wherein assisted analytics time frame data sets comprise measures of business performance data.

9. The system of claim 1 , wherein generating one or more dimension outlier factors is based on a plurality of dimension data value outlier factors derived for different dimension data values.

10. The system of claim 1 , wherein at least one dimension in the set of dimensions defines a plurality of dimension data values.

11. A computer implemented method comprising:

computing with a processor an outlier boundary for a dimension data value by applying statistical analysis to at least a portion of data organized under the dimension data value as assisted analytics time frame data sets;

detecting with the processor at least one outlier in the assisted analytics time frame data sets that is outside of the dimension data value outlier boundary;

producing a dimension data value outlier factor based on a weighting associated with an assisted analytics time frame for each of the at least one outlier;

generating one or more dimension outlier factors based at least in part on the dimension data value outlier factor derived from the detected at least one outlier; and

mapping with the processor the one or more dimension outlier factors to a corresponding dimension impact rating value, the mapping structured to facilitate user-controllable visualization in an electronic interface of an impact of each of a set of dimensions of the data organized under the dimension data value for a portion of the assisted analytics time frame data sets.

12. The method of claim 11 , wherein applying the statistical analysis to at least a portion of the data organized under the dimension data value includes calculating a standard deviation of data entries organized by the dimension data value.

13. The method of claim 12 , wherein the dimension data value outlier boundary is computed via application of a multiple of the standard deviation.

14. The method of claim 11 , wherein applying the statistical analysis is based on at least one of a size of a data structure for the assisted analytics time frame data sets, a user preference, a previously used statistical analysis, or a user ranking of the statistical analysis.

15. The method of claim 11 , wherein applying the statistical analysis is based at least in part on a count of outliers.

16. The method of claim 11 , wherein the assisted analytics time frame data sets comprise measures of business performance data.

17. The method of claim 11 , wherein the weighting is based on one or more of a recency of the time frame, a business cycle, or an importance of the dimension data value to a focus of business performance.

18. A computer implemented method comprising:

computing with a processor an outlier boundary for a dimension data value by applying statistical analysis to at least a portion of data organized under the dimension data value as assisted analytics time frame data sets;

producing a dimension data value outlier factor based on a weighting associated with each assisted analytics time frame that includes an outlier that is outside of the dimension data value outlier boundary;

generating one or more dimension outlier factors for a dimension that is common to a plurality of dimension data values based at least in part on corresponding dimension data value outlier factors; and

mapping with the processor the one or more dimension outlier factors to a corresponding dimension impact rating value, the mapping structured to facilitate user-controllable visualization in an electronic interface of an impact of each of a set of the dimensions for a portion of the assisted analytics time frame data sets.

19. The method of claim 18 , wherein the assisted analytics time frame data sets comprise measures of business performance data.

20. The method of claim 18 , wherein the dimension impact rating value is indicative of a contribution of a business process indicated by a dimension that corresponds to the impact rating value to the outlier.