DOMAIN INDEPENDENT SYSTEM AND METHOD OF AUTOMATING DATA AGGREGATION AND PRESENTATION

• US 20080275866A1
• Filed: 10/29/2007
• Published: 11/06/2008
• Est. Priority Date: 10/30/2006
• Status: Active Grant

• Current Assignee: Execue Incorporated
• Original Assignee: Execue Incorporated
• Inventors: Dasari, Viswanath, Pragada, Sreenivasa R.
• Granted Patent: US 7,885,972 B2
• Time in Patent Office: Days
• US Class Current: 707/5
• CPC Class Codes: G06F 16/24556 Aggregation; Duplicate elimination
• CPC Class Codes: G06F 16/2457 with adaptation to user needs
• CPC Class Codes: G06F 16/248 Presentation of query results
• CPC Class Codes: G06Q 10/10 Office automation; Time management

Abstract

A domain independent system and method for automatically generating at least one presentation-ready report from either detailed or summarized data from database queries. The process of getting useful information requires querying a database to get detailed records, then meaningfully aggregating detailed data based on user experience and business needs and, finally, presenting the data using appropriate reports. This process of data aggregation and presentation can be automated and is accomplished by aggregating detailed data using domain metrics selected based on predefined and configurable rules or past usage; selecting one or more presentations based on predefined and configurable rules or past usage; and displaying one or more presentations based on device constraints and characteristics.

Claims

1. A computer automated method of aggregating and presenting data, said method comprising:

inputting a set of user-defined instructions into a computer database system;

inputting a user query into said computer database system;

mining said computer database system for data relevant to said user query;

creating a data set comprising said data relevant to said user query;

aggregating data in said data set using domain metrics selected based on any of predefined and configurable rules and past user usage, wherein the aggregation comprises;

tagging all data attributes in said data set based on database metadata and inputs from a user, wherein said data attributes comprise any of data identifications (IDs), data grouping attributes, and data measure attributes, wherein the tagging process comprises inputting said user query, said database metadata for said data attributes in said user query, and attributes specifications; and

reducing the number of the tagged data attributes in said data set by logically eliminating data attributes;

selecting at least one presentation report for compiling the aggregated data, wherein the selection is based on any of predefined and configurable rules and past user usage; and

displaying said at least one presentation report to said user, wherein the displaying process comprises graphically arranging said at least one presentation report based on an available viewing area of a device accessing said at least one presentation report.

2. The method of claim 1, all the limitations of which are incorporated herein by reference, wherein said set of instructions comprise:

a structured query language (SQL) data format for processing said set of user-defined instructions;

database metadata associated with said data attributes of said computer database system; and

user input instructions identifying instructions of how an attribute is to be grouped and presented.

3. The method of claim 2, all the limitations of which are incorporated herein by reference, further comprising representing said domain metrics as any of database columns and column attributes.

4. The method of claim 3, all the limitations of which are incorporated herein by reference, further comprising categorizing each said data relevant to said user query in said data set into non-overlapping data regions.

5. The method of claim 4, all the limitations of which are incorporated herein by reference, further comprising calculating the number of unique values in said data set associated with a given attribute.

6. The method of claim 5, all the limitations of which are incorporated herein by reference, further comprising:

setting a maximum number of combination of said data attributes to be presented in said at least one presentation report;

setting a maximum number of datapoints in said data set to be presented in said at least one presentation report;

setting a maximum number of said domain metrics; and

computing a total number of combination of the tagged data attributes based on said data grouping attributes and data measure attributes.

7. The method of claim 6, all the limitations of which are incorporated herein by reference, further comprising determining whether said total number of combination of said tagged data attributes is greater than said maximum number of combination of said data attributes.

8. The method of claim 7, all the limitations of which are incorporated herein by reference, further comprising determining whether tagged data attributes exist that are not relevant to said user query.

9. The method of claim 8, all the limitations of which are incorporated herein by reference, further comprising removing the irrelevant tagged data attributes from said data set.

10. The method of claim 8, all the limitations of which are incorporated herein by reference, further comprising removing said tagged data attributes comprising the highest said unique values in said data set.

11. The method of claim 1, all the limitations of which are incorporated herein by reference, wherein for each of said data attributes in said user query, said tagging process comprises tagging the data attribute as an ID when said attribute is to be treated as an ID based on inputs to any of said computer database system and said database metadata.

12. The method of claim 1, all the limitations of which are incorporated herein by reference, wherein for each of said data attributes in said user query, said tagging process comprises applying default statistics when user specified statistics are unavailable and tagging the data attribute as a measure when said data attribute is to be treated as a measure based on inputs to any of said computer database system and said database metadata.

13. The method of claim 1, all the limitations of which are incorporated herein by reference, wherein for each of said data attributes in said user query, said tagging process comprises tagging the data attribute as a grouping attribute when said data attribute is to be treated as a grouping attribute based on inputs to any of said computer database system and said database metadata.

14. The method of claim 13, all the limitations of which are incorporated herein by reference, wherein when said data attribute comprises a grouping attribute and has a number of unique values less than the maximum numbers of unique values allowed to select a database attribute as a grouping attribute, said tagging process comprises tagging said data attribute as grouping attribute.

15. The method of claim 13, all the limitations of which are incorporated herein by reference, further comprising applying user defined ranges as grouping ranges and tagging said data attribute as a grouping attribute when said user defined ranges are available for said data attribute.

16. The method of claim 15, all the limitations of which are incorporated herein by reference, further comprising determining appropriate grouping ranges based on a distribution of said data attribute.

17. The method of claim 1, all the limitations of which are incorporated herein by reference, wherein for each of said data attributes in said user query, said tagging process comprises checking the data attribute for grouping candidacy and for any available user defined ranges when no information is input as to how said data attribute is to be treated.

18. The method of claim 17, all the limitations of which are incorporated herein by reference, further comprising tagging said data attribute as a grouping attribute when the checking process results in the identification of any of said grouping candidacy and said any available user defined ranges.

19. The method of claim 17, all the limitations of which are incorporated herein by reference, further comprising tagging said data attribute as a measure with default statistics when the checking process results in no identification of any of said grouping candidacy and said any available user defined ranges.

20. A program storage device readable by computer, tangibly embodying a program of instructions executable by said computer to perform an automated method of aggregating and presenting data, said method comprising:

inputting a set of user-defined instructions into a computer database system;

inputting a user query into said computer database system;

mining said computer database system for data relevant to said user query;

creating a data set comprising said data relevant to said user query;

aggregating data in said data set using domain metrics selected based on any of predefined and configurable rules and past user usage, wherein the aggregation comprises;

tagging all data attributes in said data set based on database metadata and inputs from a user, wherein said data attributes comprise any of data identifications (IDs), data grouping attributes, and data measure attributes, wherein the tagging process comprises inputting said user query, said database metadata for said data attributes in said user query, and attributes specifications; and

reducing the number of the tagged data attributes in said data set by logically eliminating data attributes;

selecting at least one presentation report for compiling the aggregated data, wherein the selection is based on any of predefined and configurable rules and past user usage; and

displaying said at least one presentation report to said user, wherein the displaying process comprises graphically arranging said at least one presentation report based on an available viewing area of a device accessing said at least one presentation report.

21. A system of aggregating and presenting data, said system comprising:

a user interface adapted to have a set of user-defined instructions and a user query input therein;

a computer database system adapted to be mined for data relevant to said user query;

a data set comprising said data relevant to said user query;

a logic component adapted to aggregate data in said data set using domain metrics selected based on any of predefined and configurable rules and past user usage, wherein said logic component adapted to aggregate said data comprises;

a first processing unit adapted to tag all data attributes in said data set based on database metadata and inputs from a user, wherein said data attributes comprise any of data identifications (IDs), data grouping attributes, and data measure attributes, wherein said first processing unit is adapted to have said user query, said database metadata for said data attributes in said user query, and attributes specifications being input therein; and

a second processing unit adapted to reduce the number of the tagged data attributes in said data set by logically eliminating data attributes;

a presentation report generator adapted to select at least one presentation report for compiling the aggregated data, wherein the selection is based on any of predefined and configurable rules and past user usage; and

a display unit adapted to (i) display said at least one presentation report to said user, and (ii) graphically arrange said at least one presentation report based on an available viewing area of a device accessing said at least one presentation report.

22. The system of claim 21, all the limitations of which are incorporated herein by reference, wherein said set of instructions comprise:

a structured query language (SQL) data format for processing said set of user-defined instructions;

database metadata associated with said data attributes of said computer database system; and

user input instructions identifying instructions of how an attribute is to be grouped and presented,

wherein said domain metrics are represented as any of database columns and column attributes,

wherein said logic component is adapted to categorize each said data relevant to said user query in said data set into non-overlapping data regions, and

wherein said logic component is adapted to calculate the number of unique values in said data set associated with a given attribute.

23. The system of claim 22, all the limitations of which are incorporated herein by reference, wherein said logic component is adapted to:

set a maximum number of combination of said data attributes to be presented in said at least one presentation report;

set a maximum number of datapoints in said data set to be presented in said at least one presentation report;

set a maximum number of said domain metrics; and

compute a total number of combination of the tagged data attributes based on said data grouping attributes and data measure attributes,

wherein said logic component is adapted to determine whether said total number of combination of said tagged data attributes is greater than said maximum number of combination of said data attributes,

wherein said logic component is adapted to determine whether tagged data attributes exist that are not relevant to said user query,

wherein said second processing unit is adapted to remove the irrelevant tagged data attributes from said data set, and

wherein said second processing unit is adapted to remove said tagged data attributes comprising the highest said unique values in said data set.

24. The system of claim 21, all the limitations of which are incorporated herein by reference, wherein for each of said data attributes in said user query, said first processing unit is adapted to tag the data attribute as an ID when said attribute is to be treated as an ID based on inputs to any of said computer database system and said database metadata, wherein for each of said data attributes in said user query, said first processing unit is adapted to apply default statistics when user specified statistics are unavailable and tag the data attribute as a measure when said data attribute is to be treated as a measure based on inputs to any of said computer database system and said database metadata, wherein for each of said data attributes in said user query, said first processing unit is adapted to tag the data attribute as a grouping attribute when said data attribute is to be treated as a grouping attribute based on inputs to any of said computer database system and said database metadata, wherein when said data attribute comprises a grouping attribute and has a number of unique values less than the maximum numbers of unique values allowed to select a database attribute as a grouping attribute, said first processing unit being adapted to tag said data attribute as grouping attribute, wherein said first processing unit is adapted to apply user defined ranges as grouping ranges and tag said data attribute as a grouping attribute when said user defined ranges are available for said data attribute, and wherein said first processing unit is adapted to determine appropriate grouping ranges based on a distribution of said data attribute.

25. The system of claim 21, all the limitations of which are incorporated herein by reference, wherein for each of said data attributes in said user query, said first processing unit is adapted to check the data attribute for grouping candidacy and for any available user defined ranges when no information is input as to how said data attribute is to be treated, wherein said first processing unit is adapted to tag said data attribute as a grouping attribute when the checking process results in the identification of any of said grouping candidacy and said any available user defined ranges, and wherein said first processing unit is adapted to tag said data attribute as a measure with default statistics when the checking process results in no identification of any of said grouping candidacy and said any available user defined ranges.