# US 2015/0178366 A1 · Data generation for performance evaluation > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 2015/0178366 A1 - Document ID: US20150178366A1 - Status: Published application - Kind: A1 - Application number: 14/334,069 - Filed: 2014-07-17 - Published: 2015-06-25 - Earliest claimed: 2013-12-23 - Assignees: Sap SE - Inventors: Roozbeh Farahbod; Aryan Dadashi - Web page: https://patentgrep.com/patent/US20150178366A1 ## CPC - G06F 16/217: {Database tuning (G06F16/2282 takes precedence; database performance monitoring G06F11/3409)} - G06F 11/3414: {Workload generation, e.g. scripts, playback} - G06F 11/3447: {Performance evaluation by modeling} - G06F 2201/80: Database-specific techniques - G06F: ELECTRIC DIGITAL DATA PROCESSING (computer systems based on specific computational models G06N) ## Abstract The present disclosure describes methods, systems, and computer program products for generating data for performance evaluation. One computer-implemented method includes identifying a source dataset from a source database, extracting a schema defining the source database, analyzing data within the source dataset to generate a value model, the value model describing features of data in each column of each table of the source dataset, analyzing data within the source database to determine data dependency, and generating a data specification file combining the extracted schema, the value model, and the data dependencies. ## Claims ### Claim 1 A computer-implemented method executed by one or more processors, the method comprising: identifying a source dataset from a source database; extracting a schema defining the source database; analyzing data within the source dataset to generate a value model, the value model describing features of data in each column of each table of the source dataset; analyzing data within the source database to determine data dependency; and generating a data specification file combining the extracted schema, the value model, and the data dependencies. ### Claim 2 (depends on 1) The method of claim 1, wherein determining data dependency comprises determining one or more of inter-table dependency, intra-table dependency, or inter-column dependency of data within the source database. ### Claim 3 (depends on 1) The method of claim 1, comprising storing the data specification file in a database or writing the data specification file in a file accessible by a user. ### Claim 4 (depends on 1) The method of claim 1, comprising generating synthetic data based on the data specification file, wherein the generated synthetic data corresponds to the extracted schema of the source database, wherein the generated synthetic data corresponds to the generated value model of the source database, wherein the generated synthetic data corresponds to the determined data dependency, and wherein the generated synthetic data includes different data than the analyzed data within the source database. ### Claim 5 (depends on 4) The method of claim 4, wherein the generated synthetic data has a smaller size, a same size, or a larger size than the analyzed data. ### Claim 6 (depends on 4) The method of claim 4, wherein generating synthetic data comprises: identifying a data source; identifying a value model for the synthetic data based on the generated value model of the source database; generating a composite value model based on the determined data dependency; and generating row values of the synthetic data based on the data source, the value model, and the composite value model. ### Claim 7 (depends on 4) The method of claim 4, wherein generating synthetic data comprises: generating a foreign key graph; and generating a data tables in an order according to the foreign key graph. ### Claim 8 A non-transitory, computer-readable medium storing computer-readable instructions executable by a computer and configured to: identify a source dataset from a source database; extract a schema defining the source database; analyze data within the source dataset to generate a value model, the value model describing features of data in each column of each table of the source dataset; analyze data within the source database to determine data dependency; and generate a data specification file combining the extracted schema, the value model, and the data dependencies. ### Claim 9 (depends on 8) The medium of claim 8, wherein determining data dependency comprises determining one or more of inter-table dependency, intra-table dependency, or inter-column dependency of data within the source database. ### Claim 10 (depends on 8) The medium of claim 8, comprising instructions to store the data specification file in a database or write the data specification file in a file accessible by a user. ### Claim 11 (depends on 8) The medium of claim 8, comprising instructions to generate synthetic data based on the data specification file, wherein the generated synthetic data corresponds to the extracted schema of the source database, wherein the generated synthetic data corresponds to the generated value model of the source database, wherein the generated synthetic data corresponds to the determined data dependency, and wherein the generated synthetic data includes different data than the analyzed data within the source database. ### Claim 12 (depends on 11) The medium of claim 11, wherein the generated synthetic data has a smaller size, a same size, or a larger size than the analyzed data. ### Claim 13 (depends on 11) The medium of claim 11, wherein generating synthetic data comprises: identifying a data source; identifying a value model for the synthetic data based on the generated value model of the source database; generating a composite value model based on the determined data dependency; and generating row values of the synthetic data based on the data source, the value model, and the composite value model. ### Claim 14 (depends on 11) The medium of claim 11, wherein generating synthetic data comprises: generating a foreign key graph; and generating a data tables in an order according to the foreign key graph. ### Claim 15 A system, comprising: a memory; at least one hardware processor interoperably coupled with the memory and configured to: identify a source dataset from a source database; extract a schema defining the source database; analyze data within the source dataset to generate a value model, the value model describing features of data in each column of each table of the source dataset; analyze data within the source database to determine data dependency; and generate a data specification file combining the extracted schema, the value model, and the data dependencies. ### Claim 16 (depends on 15) The system of claim 15, wherein determining data dependency comprises determining one or more of inter-table dependency, intra-table dependency, or inter-column dependency of data within the source database. ### Claim 17 (depends on 15) The system of claim 15, comprising instructions to store the data specification file in a database or write the data specification file in a file accessible by a user. ### Claim 18 (depends on 15) The system of claim 15, comprising instructions to generate synthetic data based on the data specification file, wherein the generated synthetic data corresponds to the extracted schema of the source database, wherein the generated synthetic data corresponds to the generated value model of the source database, wherein the generated synthetic data corresponds to the determined data dependency, and wherein the generated synthetic data includes different data than the analyzed data within the source database. ### Claim 19 (depends on 18) The medium of claim 18, wherein the generated synthetic data has a smaller size, a same size, or a larger size than the analyzed data. ### Claim 20 (depends on 18) The medium of claim 18, wherein generating synthetic data comprises: identifying a data source; identifying a value model for the synthetic data based on the generated value model of the source database; generating a composite value model based on the determined data dependency; generating a foreign key graph; and generating row values of the synthetic data based on the data source, the value model, the composite value model and the foreign key graph.