Smarter business intelligence systems

• US 8,682,825 B2
• Filed: 07/21/2012
• Issued: 03/25/2014
• Est. Priority Date: 01/24/2011
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Negi, Sumit, Bhide, Manish Anand, Batra, Vishal Singh, Kothari, Govind
• Primary Examiner(s): Gaffin, Jeffrey A
• Assistant Examiner(s): FINK, THOMAS ANDREW
• Application Number:
  US13/555,121
• Publication Number:
  US 20120290345A1
• Time in Patent Office: 612 Days
• Field of Search: 706/46, 709/223, 709/224
• US Class Current: 706/45
• CPC Class Codes: G06Q 10/00 Administration; Management

Abstract

An embodiment of the invention provides a method and system for analyzing a plurality of reports. More specifically, a change detection module predicts results of future reports based on past reports and identifies a first report that deviates from its predicted results. A dependency analysis module connected to the change detection module at least one report sharing a dependency with the first report by performing a dependency analysis and/or a usage analysis. The dependency analysis labels the first report and at least one second report as sharing a dependency if the second report deviates from its predicted results. The usage analysis labeling the first report and at least one report analyzed by an analyst as sharing a dependency if the report analyzed by the analyst is analyzed in response to the identification of the first report.

Claims

1. A system for analyzing a plurality of reports, said system comprising:

a change detection module on a processor that predicts results of future reports based on past reports and identifying a first report that deviates from its predicted results;

a dependency analysis module on a processor, said dependency analysis module connected to said change detection module, said dependency analysis module performs a usage analysis, the usage analysis identifies at least one report that has previously been analyzed by an a human analyst, the report that has previously been analyzed by the human analyst having been requested by the human analyst in response to the identifying of the first report as deviating from its predicted results, the usage analysis, subsequent to said identifying at least one report that has previously been analyzed by a human analyst, labels the first report and the at least one report analyzed by the human analyst as sharing a dependency based on the fact that said at least one report that has previously been analyzed by a human analyst was requested by the human analyst in response to said identifying of the first report.

2. The system according to claim 1, wherein said dependency analysis module performs at least one of:

identifying at least one sub-component of the first report and at least one sub-component of the at least one second report that share a dependency when a dependency analysis is performed; and

identifying at least one sub-component of the first report and at least one sub-component of the at least one report analyzed by the human analyst that share a dependency when the usage analysis is performed.

3. The system according to claim 1, wherein said dependency analysis module:

analyzes at least one dependent report, the dependent report sharing a dependency with a select report, and calculates a deviation for each of the sub-components of the dependent report that deviate from the predicted results of the dependent report; and

ranks the sub-components of the dependent report based on the calculated deviations.

4. The system according to claim 3, wherein the select report is the first report, the at least one second report, or the at least one report analyzed by the human analyst.

5. The system according to claim 3, wherein said dependency analysis module:

analyzes at least one second dependent report, the second dependent report sharing a dependency with the dependent report, and calculates a deviation for each of the sub-components of the second dependent report that deviate from the predicted results of the second dependent report; and

ranks the sub-components of the dependent report and the sub-components of the second dependent report based on the calculated deviations.

6. A computer program product for analyzing a plurality of reports, said computer program product comprising:

a non-transitory computer readable storage medium;

first program instructions to predict results of future reports based on past reports;

second program instructions to identify a first report that deviates from its predicted results; and

third program instructions to perform a usage analysis, said usage analysis including;

identifying at least one report that has previously been analyzed by a human analyst, said report that has previously been analyzed by a human analyst having been requested by the human analyst in response to said identifying of the first report, and

subsequent to said identifying at least one report that has previously been analyzed by a human analyst, labeling the first report and the at least one report that has previously been analyzed by the human analyst as sharing a dependency based on the fact that said at least one report that has previously been analyzed by a human analyst was requested by the human analyst in response to said identifying of the first report,

said first program instructions, said second program instructions, and said third program instructions are stored on said computer readable storage medium.

7. The computer program product according to claim 6, further comprising:

fourth program instructions to, when a dependency analysis is performed, identify at least one sub-component of the first report and at least one sub-component of the at least one second report that share a dependency; and

fifth program instructions to, when the usage analysis is performed, identify at least one sub-component of the first report and at least one sub-component of the at least one report analyzed by the human analyst that share a dependency.

8. The computer program product according to claim 6, further comprising:

sixth program instructions to analyze at least one dependent report, the dependent report sharing a dependency with the select report, the analysis of the at least one dependent report including calculating a deviation for each of the sub-components of the dependent report that deviate from the predicted results of the dependent report; and

seventh program instructions to rank the sub-components of the dependent report based on the calculated deviations.

9. The computer program product according to claim 8, wherein the select report is the first report, the at least one second report, or the at least one report analyzed by the human analyst.

10. The computer program product according to claim 8, further comprising, when the at least one dependent report has a threshold deviation from the predicted results of the dependent report:

eighth program instructions to analyze at least one second dependent report, the second dependent report sharing a dependency with the dependent report, said analyzing of the at least one second dependent report including calculating a deviation for each of the sub-components of the second dependent report that deviate from the predicted results of the second dependent report; and

ninth program instructions to rank the sub-components of the dependent report and the sub-components of the second dependent report based on the calculated deviations.

11. A system for analyzing a plurality of reports, said system comprising:

a change detection module on a processor that predicts results of future reports based on past reports and identifying a first report that deviates from its predicted results;

a dependency analysis module on a processor connected to said change detection module,

said dependency analysis module performs a usage analysis, the usage analysis identifies at least one report that has previously been analyzed by a human analyst, the report that has previously been analyzed by the human analyst having been requested by the human analyst in response to the identifying of the first report as deviating from its predicted results, the usage analysis, subsequent to said identifying at least one report that has previously been analyzed by a human analyst, labels the first report and the at least one report that has previously been analyzed by the human analyst as sharing a dependency based on the fact that said at least one report that has previously been analyzed by a human analyst was requested by the human analyst in response to said identifying of the first report,

said dependency analysis module performs at least one of;

identifying at least one sub-component of the first report and at least one sub-component of the at least one second report that share a dependency when the dependency analysis is performed; and

identifying at least one sub-component of the first report and at least one sub-component of the at least one report that has previously been analyzed by the human analyst that share a dependency when the usage analysis is performed.

12. The system according to claim 11, wherein said dependency analysis module:

analyzes at least one dependent report, the dependent report sharing a dependency with a select report, and calculates a deviation for each of the sub-components of the dependent report that deviate from the predicted results of the dependent report; and

ranks the sub-components of the dependent report based on the calculated deviations.

13. The system according to claim 12, wherein the select report is the first report, the at least one second report, or the at least one report analyzed by the human analyst.

14. The system according to claim 12, wherein said dependency analysis module:

analyzes at least one second dependent report, the second dependent report sharing a dependency with the dependent report, and calculates a deviation for each of the sub-components of the second dependent report that deviate from the predicted results of the second dependent report; and

ranks the sub-components of the dependent report and the sub-components of the second dependent report based on the calculated deviations.