Enhanced processing of large data volumes from inside relational databases
This disclosure describes systems, methods, and devices related to analyzing data stored in a relational database. A method may include installing a structured query language (SQL) server on a host server; installing statistical analysis modules on the host server; executing the statistical analysis modules within a relational database of the SQL server to analyze data stored in the relational database; and generating outputs based on the execution of the statistical analysis modules within the relational database.
1. A method for analyzing data stored in a relational database, the method comprising:
installing a structured query language (SQL) server application on a host server;
installing statistical analysis modules on the host server;
executing the statistical analysis modules within a relational database of the SQL server application to analyze data stored in the relational database;
generating outputs based on the execution of the statistical analysis modules within the relational database;
generating a data mart in the SQL server application, the data mart comprising financial data, wherein the data comprises the financial data;
generating a conceptual data model comprising independent specifications of the financial data;
generating, based on the conceptual data model, a logical data model indicative of structures of the financial data to be implemented in the relational database; and
generating, based on the logical data model, a physical data model in which the financial data are organized into tables, wherein generating the data mart is based on the tables.
2. The method of claim 1 , wherein generating the outputs occurs without exporting the data stored in the relational database.
3. The method of claim 1 , wherein the host server comprises 32 processing cores and 64 gigabytes of random access memory.
4. The method of claim 1 , wherein the outputs comprise a spending trend and a forecast budget run rate.
5. The method of claim 1 , wherein the statistical analysis modules use an R statistical model.
6. A system for analyzing data stored in a relational database, the system comprising memory coupled to at least one processor of a host server, the at least one processor configured to:
install a structured query language (SQL) server application on the host server;
install statistical analysis modules on the host server;
execute the statistical analysis modules within a relational database of the SQL server application to analyze data stored in the relational database;
generate outputs based on the execution of the statistical analysis modules within the relational database;
generate a data mart in the SQL server application, the data mart comprising financial data, wherein the data comprises the financial data;
generate a conceptual data model comprising independent specifications of the financial data;
generate, based on the conceptual data model, a logical data model indicative of structures of the financial data to be implemented in the relational database; and
generate, based on the logical data model, a physical data model in which the financial data are organized into tables, wherein generating the data mart is based on the tables.
7. The system of claim 6 , wherein to generate the outputs occurs without exporting the data stored in the relational database.
8. The system of claim 6 , wherein the host server comprises 32 processing cores and 64 gigabytes of random access memory.
9. The system of claim 6 , wherein the outputs comprise a spending trend and a forecast budget run rate.
10. The system of claim 6 , wherein the statistical analysis modules use an R statistical model.
11. A non-transitory computer-readable storage medium comprising instructions to cause at least one processor of a device for analyzing data stored in a relational database, upon execution of the instructions by the at least one processor, to:
install a structured query language (SQL) server application on a host server;
install statistical analysis modules on the host server;
execute the statistical analysis modules within a relational database of the SQL server application to analyze data stored in the relational database;
generate outputs based on the execution of the statistical analysis modules within the relational database;
generate a data mart in the SQL server application, the data mart comprising financial data, wherein the data comprises the financial data;
generate a conceptual data model comprising independent specifications of the financial data;
generate, based on the conceptual data model, a logical data model indicative of structures of the financial data to be implemented in the relational database; and
generate, based on the logical data model, a physical data model in which the financial data are organized into tables, wherein generating the data mart is based on the tables.
12. The non-transitory computer-readable storage medium of claim 11 , wherein to generate the outputs occurs without exporting the data stored in the relational database.
13. The non-transitory computer-readable storage medium of claim 11 , wherein the host server comprises 32 processing cores and 64 gigabytes of random access memory.
14. The non-transitory computer-readable storage medium of claim 11 , wherein the outputs comprise a spending trend and a forecast budget run rate.