APPARATUS AND METHOD FOR ASSESSING RELEVANT CATEGORIES AND MEASURES FOR USE IN DATA ANALYSES

• US 20080104060A1
• Filed: 10/12/2007
• Published: 05/01/2008
• Est. Priority Date: 10/31/2006
• Status: Active Grant

• Current Assignee: Business Objects Incorporated (SAP SE)
• Original Assignee: Business Objects SA (SAP SE)
• Inventors: GOSPER, Julian, AGATHOS, Jean-Luc, CHONGVILAY, Virgile, CUBRANIC, Davor, ABHYANKAR, Saurabh
• Granted Patent: US 7,899,832 B2
• Time in Patent Office: Days
• US Class Current: 707/5
• CPC Class Codes: G06F 16/3323 using document space presentation or visualization, e.g. category, hierarchy or range presentation and selection
• CPC Class Codes: Y10S 707/957 Multidimensional
• CPC Class Codes: Y10S 707/99942 Manipulating data structure, e.g. compression, compaction, compilation

Abstract

A computer readable storage medium includes executable instructions to receive a relevancy parameter. The relevancy parameter is searched in a category ensemble including a set of categories, where the category ensemble overlies a dataset. A first order of the set of categories is created based on the relevancy of the relevancy parameter to each category in the set of categories, where the relevancy is a degree of match to the relevancy parameter. A second order of the set of categories is created based on the merit of each category to partition the dataset. The first order and the second order are combined into a final order, which is returned. A measure in the category ensemble is searched based on the relevancy parameter. The measure is returned as a selected measure, where the selected measure is a codomain of a visualization depicting a portion of the dataset.

Claims

1. A computer readable storage medium, comprising executable instructions to:

receive a selection of a category ensemble overlying a dataset;

define an analysis view of the category ensemble, wherein the analysis view comprises;

a set of categories divided into;

a first subset of unselected categories, and

a second subset of selected categories,

a set of measures, and

a visualization for a subset of the dataset;

create a first order of the first subset of unselected categories based on relevancy;

create a second order of the first subset of unselected categories based on merit, wherein merit is a value which indicates efficiency for partitioning the dataset;

combine the first order and the second order into a final order for the first subset of unselected categories of the set of categories; and

display the first subset of unselected categories in the final order.

2. The computer readable storage medium of claim 1 further comprising executable instructions to:

receive a relevancy parameter; and

conduct a search based on the relevancy parameter in the category ensemble, wherein the first order based on the relevancy is based on relevancy of the relevancy parameter to each category in the set of categories.

3. The computer readable storage medium of claim 2 further comprising executable instructions to:

conduct a search based on the relevancy parameter over a plurality of category ensembles; and

order the plurality of category ensembles by relevancy.

4. The computer readable storage medium of claim 1 wherein a high value for merit is taken from the combination of two or more values selected from high entropy, high coverage and low cardinality.

5. The computer readable storage medium of claim 1, wherein relevancy is based on at least one of keyword, usage metrics, data source information, data quality level, data lineage metadata, favorite information, data design information and data metadata.

6. The computer readable storage medium of claim 5 wherein relevancy based on keyword is selected from the group comprising equality of keyword to name, similarity of keyword to name, equality of keyword to metadata, and similarity of keyword to metadata.

7. The computer readable storage medium of claim 1 further comprising executable instructions to:

accept the selection of an attribute in a category in the set of categories, wherein the category includes a set of attributes; and

filter the dataset using the attribute as a filter value.

8. The computer readable storage medium of claim 7 further comprising executable instructions to display the second subset of selected categories in a third order, wherein the third order reflects the sequence in which the categories in the second subset of selected categories were selected.

9. The computer readable storage medium of claim 7 further comprising executable instructions to determine another final order for the first subset of unselected categories.

10. The computer readable storage medium of claim 1 further comprising executable instructions to:

select a highly relevant measure in the category ensemble; and

return the highly relevant measure as a preselected measure, wherein the preselected measure is a codomain of the visualization.

11. The computer readable storage medium of claim 1 further comprising executable instructions to:

select a highly relevant category in the category ensemble; and

return the category as a preselected domain in a visualization.

12. The computer readable storage medium of claim 1 wherein the final order is selected from the group comprising:

heterogeneous in terms of the first order and the second order of the first subset of unselected categories, and

homogenous in terms of the first order and the second order of the first subset of unselected categories.

13. The computer readable storage medium of claim 1 further comprising executable instructions to:

accept the selection of a category in the set of categories; and

update the analysis view to include the category as a breakdown category.

14. The computer readable storage medium of claim 1 further comprising executable instructions to:

display the analysis view in a graphical user interface, wherein;

the first subset of unselected categories is made available for selection,

the second subset of selected categories is made available for unselection,

the set of measures is made available for selection or unselection,

a selection change includes selection and unselection, and

receive a representative selection change created by a user'"'"'s interaction with the graphical user interface; and

refresh the analysis view based on the representative selection change.

15. The computer readable storage medium of claim 1, wherein:

each of the set of measures, the set of categories and the category ensemble is associated with two or more pieces of metadata selected from;

name, multilingual name, description, user tags, user comments, usage metrics, data source information, data quality level, data lineage information, favorite information, data design information and data information.

16. A computer readable storage medium, comprising executable instructions to:

receive a relevancy parameter;

search for the relevancy parameter in a category ensemble including a set of categories, wherein the category ensemble overlies a dataset;

create a first order of the set of categories based on the relevancy of the relevancy parameter to each category in the set of categories, wherein relevancy is a degree of match to the relevancy parameter;

create a second order of the set of categories based on the merit of each category to partition the dataset;

combine the first order and the second order into a final order;

return the final order;

search for a measure in the category ensemble based on the relevancy parameter; and

return the measure as a selected measure, wherein the selected measure is a codomain of a visualization depicting a portion of the dataset.

17. The computer readable storage medium of claim 16 further comprising executable instructions to:

retrieve a dataset that underlies the category ensemble from a data source;

build an enumeration tree to represent the dataset;

calculate a plurality of merit values for the set of categories; and

store an order of the categories based on the merit values as the second order.

18. The computer readable storage medium of claim 16 wherein:

a category in the set of categories comprises a set of attributes; and

each attribute in the set of attributes is a potential filter for the dataset.

19. The computer readable storage medium of claim 16 further comprising executable instructions to preselect a category as a domain in the visualization wherein the category is highly relevant to the relevancy parameter.

20. The computer readable storage medium of claim 16 further comprising executable instructions to preselect an attribute as a filter on the dataset wherein the attribute is the only attribute matching the relevancy parameter.

21. The computer readable storage medium of claim 16 further comprising executable instructions to:

accept the selection of an attribute in a category in the set of categories, wherein the category includes a set of attributes; and

filter the dataset using the attribute as a filter value.

22. The computer readable storage medium of claim 21 further comprising executable instructions to:

transfer the category containing the selected attribute from a first subset of unselected categories of the set of categories to a second subset of selected categories of the set of categories; and

determine a new final order for the first subset of unselected categories.

23. The computer readable storage medium of claim 16 wherein the category ensemble is included in a plurality of category ensambles.

24. The computer readable storage medium of claim 23 further comprising executable instructions to:

determine the relevancy of each category ensemble in the plurality of category ensembles;

order the plurality of category ensembles by relevancy; and

return the plurality of category ensembles in order.