Schema recommendations

1 . A computer-implemented method, comprising:

analyzing, by a processor set, at least one data source from at least one database to extract characteristics for the at least one data source;

generating, by the processor set, at least one recommendation based on the extracted characteristics for the at least one data source;

performing, by the processor set, conflict resolution on the generated at least one recommendation by removing at least one conflicted recommendation in the at least one recommendation;

determining, by the processor set, a chosen recommendation (CR) set based on the conflict resolution;

ranking, by the processor set, each recommendation in the CR set based on a ranking score; and

displaying, by the processor set, a visual summary of each recommendation in the CR set.

2 . The computer-implemented method of claim 1 , further comprising:

receiving, by the processor set, a modification action; and

updating, by the processor set, at least one weight for each recommendation in the CR set based on the modification action.

3 . The computer-implemented method of claim 2 , further comprising:

re-computing, by the processor set, the CR set based on the updated at least one weight and the modification action; and

displaying, by the processor set, each recommendation in the re-computed CR set.

4 . The computer-implemented method of claim 1 , further comprising:

receiving, by the processor set, an acceptance action; and

generating, by the processor set, a generic schema recommendation based on each recommendation in the CR set and the acceptance action.

5 . The computer-implemented method of claim 4 , further comprising generating, by the processor set, a structured query language (SQL) code based on the generic schema recommendation.

6 . The computer-implemented method of claim 5 , further comprising utilizing, by the processor set, the SQL in a target database system.

7 . The computer-implemented method of claim 1 , wherein the at least one data source is selected from the group consisting of database data, query data, log data, domain knowledge data, policy document data, and application source code data.

8 . The computer-implemented method of claim 7 , further comprising assigning, by the processor set, at least one weight based on the at least one data source.

9 . The computer-implemented method of claim 8 , wherein the at least one data source comprises a plurality of data sources, and each of the plurality of data sources are assigned a different weight from remaining data sources.

10 . The computer-implemented method of claim 1 , wherein the performing the conflict resolution comprises performing a greedy approach algorithm by iterating over the generated at least one recommendation.

11 . The computer-implemented method of claim 1 , wherein the performing the conflict resolution comprises performing an optimized approach algorithm by picking a subset of the generated at least one recommendation.

12 . A computer program product comprising:

one or more computer readable storage media; and

program instructions stored on the one or more computer readable storage media to perform operations comprising:

analyzing at least one data source from at least one database to extract characteristics for the at least one data source;

generating at least one recommendation based on the extracted characteristics for the at least one data source;

performing conflict resolution on the generated at least one recommendation by removing at least one conflicted recommendation in the at least one recommendation;

determining a chosen recommendation (CR) set based on the conflict resolution;

ranking each recommendation in the CR set based on a ranking score; and

displaying a visual summary of each recommendation in the CR set.

13 . The computer program product of claim 12 , wherein the operations further comprise:

receiving a modification action; and

updating at least one weight for each recommendation in the CR set based on the modification action.

14 . The computer program product of claim 13 , wherein the operations further comprise:

re-computing the CR set based on the updated at least one weight and the modification action; and

displaying each recommendation in the re-computed CR set.

15 . The computer program product of claim 12 , wherein the operations further comprise:

receiving an acceptance action; and

generating a generic schema recommendation based on each recommendation in the CR set and the acceptance action.

16 . The computer program product of claim 15 , wherein the operations further comprise generating a structured query language (SQL) code based on the generic schema recommendation.

17 . The computer program product of claim 16 , wherein the operations further comprise utilizing the SQL in a target database system.

18 . The computer program product of claim 12 , wherein the at least one data source is selected from the group consisting of database data, query data, log data, domain knowledge data, policy document data, and application source code data.

19 . The computer program product of claim 18 , wherein the operations further comprise assigning at least one weight based on the at least one data source.

20 . A system comprising:

a processor set;

one or more computer readable storage media; and

program instructions stored on the one or more computer readable storage media to cause the processor set to perform operations comprising:

analyzing at least one data source from at least one database to extract characteristics for the at least one data source;

generating at least one recommendation based on the extracted characteristics for the at least one data source;

performing conflict resolution on the generated at least one recommendation by removing at least one conflicted recommendation in the at least one recommendation;

determining a chosen recommendation (CR) set based on the conflict resolution;

ranking each recommendation in the CR set based on a ranking score;

displaying a visual summary of each recommendation in the CR set; and

generating a structured query language (SQL) based on an approval of the displayed visual summary.