Estimating a computing job complexity

1. A non-transitory computer readable storage medium on which is embedded one or more computer programs, said one or more computer programs implementing a method for estimating a complexity of a computing job for transformation of data objects related to a first application for compatibility with a second application, said one or more computer programs comprising computer readable code for:

retrieving selected data objects related to the first application from a data repository, wherein each of the selected data objects is formed of multiple elements, wherein the selected data objects comprise at least one of mappings and graphs, wherein the multiple elements of the at least one of mappings and graphs comprise transformations each representing a transformation of the selected data objects related to the first application for compatibility with the second application and Structured Query Language (SQL) overrides;

assigning points to the multiple elements according to a predefined schedule;

calculating scores for the selected data objects by

calculating transformation scores for each of the at least one of mappings and graphs by multiplying the transformations by their respective points to obtain respective products, and summing the products, and

calculating SQL override scores for each of the at least one of mappings and graphs by determining points assigned to each of the SQL overrides based upon length ranges of the SQL overrides, wherein mapping scores comprise sums of respective transformation scores and SQL override scores;

estimating complexities of the selected data objects for transformation of the selected data objects for compatibility with the second application based upon the calculated scores and the predefined schedule;

estimating a complexity of the computing job based upon the estimated complexities of the selected data objects;

estimating an amount of resources required to perform the computing job based upon the complexity of the computing job; and

performing, based on the estimated amount of resources, the computing job to transform the selected data objects for compatibility with the second application.

2. The computer readable storage medium according to claim 1 , said one or more computer programs further comprising computer readable code for:

receiving user input pertaining to a historical knowledge of the selected data objects; and

creating the predefined schedule of points for the multiple elements, wherein the predefined schedule of points is developed from a historical knowledge of the selected data objects.

3. The computer readable storage medium according to claim 1 , wherein the computer readable code for performing the computing job to transform the selected data objects for compatibility with the second application further comprises computer readable code for

employing the estimated amount of resources in developing a bid for performing the computing job.

4. The computer readable storage medium according to claim 1 , said one or more computer programs further comprising computer readable code for

outputting a summary sheet of the estimated computing job complexity that depicts the estimated complexities of each of the selected data objects.

5. The computer readable storage medium according to claim 1 , wherein estimating complexities of the selected data objects further comprises estimating complexities of the at least one of mappings and graphs based upon the scores of each of the at least one of mappings and graphs and wherein estimating the complexity of the computing job further comprises estimating the complexity of the computing job based upon a function of the estimated complexities of each of the at least one of mappings and graphs.

6. The computer readable storage medium according to claim 5 , wherein estimating complexities of the at least one of mappings and graphs further comprises estimating the complexities of the at least one of mappings and graphs based upon where the scores for each of the at least one of mappings and graphs falls in a complexity schedule that relates ranges of scores to complexity values.

7. The computer readable storage medium according to claim 1 , wherein for the selected data objects comprising the mappings, said one or more computer programs further comprising computer readable code for:

accessing an intelligence report;

identifying relevant data from the intelligence report, wherein the relevant data comprises the transformations and the SQL overrides of the mappings; and

creating a spreadsheet with information pertaining to the relevant data, said spreadsheet facilitating retrieval of the selected data objects.

8. The computer readable storage medium according to claim 7 , wherein identifying the relevant data further comprises identifying a summary count of the transformations and lengths of the SQL overrides, and wherein creating the spreadsheet further comprises creating the spreadsheet to include the summary count of the transformations and the lengths of the SQL overrides.

9. The computer readable storage medium according to claim 1 , wherein the selected data objects further comprise business objects universes and business objects reports, and wherein the multiple elements further comprise universe components of the business objects universes and report components of the business objects reports.

10. The computer readable storage medium according to claim 9 , wherein calculating scores for the selected data objects further comprises calculating scores for each of the universe components by determining the numbers of each of the respective universe components, and wherein estimating complexities of the business objects universes further comprises:

comparing the number of universe components to the predefined schedule to determine complexities of the respective universe components, wherein the predefined schedule includes a correlation between the numbers of respective universe components and a plurality of complexity designations;

multiplying the points assigned to each of the universe components by their respective complexity designations, wherein the predefined schedule further includes a correlation between the respective universe components and the points assigned to the respective universe components; and

wherein estimating complexities of the selected data objects further comprises estimating the complexities of the business objects universes based upon the complexity designations of the respective universe components and the points assigned to the respective universe components.

11. The computer readable storage medium according to claim 9 , wherein calculating scores for the selected data objects further comprises calculating scores for each of the report components by determining the numbers of each of the respective report components, and wherein estimating complexities of the business objects universes further comprises:

comparing the number of report components to the predefined schedule to determine complexities of the respective report components, wherein the predefined schedule includes a correlation between the numbers of respective report components and a plurality of complexity designations;

multiplying the points assigned to each of the report components by their respective complexity designations, wherein the predefined schedule further includes a correlation between the respective report components and the points assigned to the respective report components; and

wherein estimating complexities of the selected data objects further comprises estimating the complexities of the business objects universes based upon the complexity designations of the respective report components and the points assigned to the respective report components.

12. The computer readable storage medium according to claim 9 , said one or more computer programs further comprising computer readable code for:

accessing an intelligence report;

identifying relevant data from the intelligence report, wherein the relevant data comprises the universe components of the business objects universes and the report components of the report universes; and

creating a spreadsheet with information pertaining to the relevant data.

13. The computer readable storage medium according to claim 12 , wherein identifying the relevant data further comprises identifying a summary count of the universe components and the report components and wherein creating the spreadsheet further comprises creating the spreadsheet to include the summary count of the universe components and the report components.

14. A processing apparatus for estimating a complexity of a computing job for transformation of data objects related to a first application for compatibility with a second application, said processing apparatus comprising:

at least one processor;

a storage device in communication with the at least one processor, said storage device storing instructions that, when executed by the at least one processor, cause the at least one processor to:

retrieve selected data objects related to the first application from a data repository, wherein each of the selected data objects is formed of multiple elements, wherein the selected data objects comprise at least one of mappings and graphs, wherein the multiple elements of the at least one of mappings and graphs comprise transformations each representing a transformation of the selected data objects related to the first application for compatibility with the second application and Structured Query Language (SQL) overrides;

assign points to the multiple elements according to a predefined schedule;

calculate scores for the selected data objects by

calculating transformation scores for each of the at least one of mappings and graphs by multiplying the transformations by their respective points to obtain respective products, and summing the products, and

calculating SQL override scores for each of the at least one of mappings and graphs by determining points assigned to each of the SQL overrides based upon length ranges of the SQL overrides, wherein at least one of mapping scores and graphs scores comprise sums of respective transformation scores and SQL override scores;

estimate complexities of the selected data objects for transformation of the selected data objects for compatibility with the second application based upon the calculated scores and the predefined schedule;

estimate a complexity of the computing job based upon the estimated complexities of the selected data objects;

estimate an amount of resources required to perform the computing job based upon the complexity of the computing job; and

perform, based on the estimated amount of resources, the computing job to transform the selected data objects for compatibility with the second application.

15. The processing apparatus according to claim 14 , said storage device further storing instructions that, when executed by the at least one processor, cause the at least one processor to:

create the predefined schedule of points for the multiple elements from a user's historical knowledge of the selected data objects.

16. The processing apparatus according to claim 14 , said storage device further storing instructions that, when executed by the at least one processor, cause the at least one processor to:

estimate complexities of the at least one of mappings and graphs based upon the scores of each of the at least one of mappings and graphs and wherein estimating the complexity of the computing job further comprises estimating the complexity of the computing job based upon a function of the estimated complexities of each of the at least one of mappings and graphs.

17. The processing apparatus according to claim 14 , said storage device further storing instructions that, when executed by the at least one processor, cause the at least one processor to:

estimate complexities of the at least one of mappings and graphs based upon the scores of each of the at least one of mappings and graphs, and wherein estimating the complexities of the at least one of mappings and graphs further comprises estimating the complexities of the at least one of mappings and graphs based upon where the scores for each of the at least one of mappings and graphs falls in a complexity schedule that relates ranges of scores to complexity values.

18. The processing apparatus according to claim 14 , wherein for the selected data objects comprising the mappings, said storage device further storing instructions that, when executed by the at least one processor, cause the at least one processor to:

access an intelligence report;

identify relevant data from the intelligence report, wherein the relevant data comprises the transformations and the SQL overrides of the mappings; and

create a spreadsheet with information pertaining to the relevant data, wherein the spreadsheet facilitates retrieval of the selected data objects.

19. The processing apparatus according to claim 14 , wherein the selected data objects further comprise business objects universes and business objects reports, and wherein the multiple elements further comprise universe components of the business objects universes and report components of the business objects reports.

20. The processing apparatus according to claim 19 , said storage device further storing instructions that, when executed by the at least one processor, cause the at least one processor to:

calculate scores for each of the universe components by determining the numbers of each of the respective universe components; and

estimate complexities of the business objects universes by,

comparing the number of universe components to the predefined schedule to determine complexities of the respective universe components, wherein the predefined schedule includes a correlation between the numbers of respective universe components and a plurality of complexity designations;

multiplying the points assigned to each of the universe components by their respective complexity designations, wherein the predefined schedule further includes a correlation between the respective universe components and the points assigned to the respective universe components; and

estimating the complexities of the business objects universes based upon the complexity designations of the respective universe components and the points assigned to the respective universe components.

21. The processing apparatus according to claim 19 , said storage device further storing instructions that, when executed by the at least one processor, cause the at least one processor to:

calculate scores for each of the report components by determining the numbers of each of the respective report components; and

estimate complexities of the business objects universes by,

comparing the number of report components to the predefined schedule to determine complexities of the respective report components, wherein the predefined schedule includes a correlation between the numbers of respective report components and a plurality of complexity designations;

multiplying the points assigned to each of the report components by their respective complexity designations, wherein the predefined schedule further includes a correlation between the respective report components and the points assigned to the respective report components; and

estimating the complexities of the business objects universes based upon the complexity designations of the respective report components and the points assigned to the respective report components.

22. The processing apparatus according to claim 19 , said storage device further storing instructions that, when executed by the at least one processor, cause the at least one processor to:

access an intelligence report;

identify relevant data from the intelligence report, wherein the relevant data comprises the universe components of the business objects universes and the report components of the report universes; and

create a spreadsheet with information pertaining to the relevant data.

23. The processing apparatus according to claim 22 , said storage device further storing instructions that, when executed by the at least one processor, cause the at least one processor to:

identify a summary count of the universe components and the report components and create the spreadsheet to include the summary count of the universe components and the report components.

24. A method for estimating a complexity of a computing job for transformation of data objects related to a first application for compatibility with a second application, the method comprising:

retrieving selected data objects related to the first application from a data repository, wherein each of the selected data objects is formed of multiple elements, wherein the selected data objects comprise at least one of mappings and graphs, wherein the multiple elements of the at least one of mappings and graphs comprise transformations each representing a transformation of the selected data objects related to the first application for compatibility with the second application and Structured Query Language (SQL) overrides;

assigning points to the multiple elements according to a predefined schedule;

calculating scores for the selected data objects by

calculating transformation scores for each of the at least one of mappings and graphs by multiplying the transformations by their respective points to obtain respective products, and summing the products, and

calculating SQL override scores for each of the at least one of mappings and graphs by determining points assigned to each of the SQL overrides based upon length ranges of the SQL overrides, wherein at least one of mapping scores and graphs scores comprise sums of respective transformation scores and SQL override scores;

estimating complexities of the selected data objects for transformation of selected data objects for compatibility with the second application based upon the calculated scores and the predefined schedule;

estimating, by a processor, the complexity of the computing job based upon the estimated complexities of the selected data objects;

estimating an amount of resources required to perform the computing job based upon the complexity of the computing job; and

performing, based on the estimated amount of resources, the computing job to transform the selected data objects for compatibility with the second application.

25. The computer readable storage medium according to claim 1 , wherein the selected data objects comprise predetermined file extensions.

26. The computer readable storage medium according to claim 1 , wherein the lengths of the SQL overrides are calculated from a from clause to an end of a select statement.