Platform for integrating back-end data analysis tools using schema

1. A computer-implemented method, comprising:

generating and displaying a graphical user interface including one or more selectable generic options that indicate functions of a data system that may be selected for integration with other functions;

receiving a selection of a plurality of data analysis functions from among the selectable generic options;

receiving user selections that assemble an application in an application window of the graphical user interface, wherein the application is assembled to create a hybrid approach to extract product attributes that combines both image and text description, and wherein the application includes one of the selected data analysis functions;

translating the selected data analysis functions into pre-configured commands for a plurality of back-end tools for performing the selected data analysis functions based on a mapping between the selected data analysis function and the pre-configured commands, wherein the pre-configured commands back-end data sets through synonyms for fields of the back-end data sets;

executing the preconfigured commands to create the synonyms;

executing the selected data analysis function on the synonyms for the fields of the back-end data from the plurality of back-end tools and generate a data analysis result of the combined functionality of the data analysis functions; and

creating a restful service definition for the data analysis result that shares the data analysis result to other processes.

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

receiving a selection of a second data analysis function;

receiving a selection describing a combination of the data analysis function and the second data analysis function; and

executing the second data analysis function in relation to the data analysis function in accordance with the described combination in order to perform a combined functionality of the data analysis functions.

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

receiving a selection of a code editor;

receiving an entry of software code to create a second function;

receiving a selection describing a combination of the data analysis function and the second function; and

executing the second function in relation to the data analysis function in accordance with the described combination in order to perform a combined functionality of the data analysis function and the second function.

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

receiving a selection of a visualization function;

receiving a selection describing a combination of the data analysis function and the visualization function; and

executing the visualization function in relation to the data analysis function in accordance with the described combination to display a result of the data analysis function.

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

receiving a selection of a report function;

receiving a selection describing a combination of the data analysis function and the report function; and

executing the report function in relation to the data analysis function in accordance with the described combination to generate a report describing a result of the data analysis function.

6. The computer-implemented method of claim 1 , wherein the back-end data sets are retail-specific data that include aggregate retail data.

7. A non-transitory computer-readable medium storing computer-executable instructions that, when executed by at least a processor of a computer, cause the computer to:

generate and display a graphical user interface including one or more selectable generic options that indicate functions of a data system that may be selected for use with other functions;

receive a selection of a data analysis function from among the selectable generic options;

receive user selections that assemble an application in an application window of the graphical user interface, wherein the application is assembled to display affinities between products in a basket as a graph, and wherein the application includes the selected data analysis function;

translate the selected data analysis function into pre-configured commands for a plurality of back-end tools for performing the selected data analysis function, wherein the pre-configured commands identify and access specific schema with a compatible format for reading the specific schema from each of the plurality of back-end tools to expose back-end data sets through synonyms for fields of the back-end data sets;

execute the preconfigured commands to create the synonyms;

execute the selected data analysis function on the synonyms for the fields of the back-end data sets from the plurality of back-end tools and generate a data analysis result; and

create a restful service definition for the data analysis result that shares the data analysis result to other processes.

8. The non-transitory computer readable medium of claim 7 , wherein the instructions further cause the computer to:

receive a selection of a second data analysis function;

receive a selection describing a combination of the data analysis function and the second data analysis function; and

execute the second data analysis function in relation to the data analysis function in accordance with the described combination in order to perform a combined functionality of the data analysis functions.

9. The non-transitory computer readable medium of claim 7 , wherein the instructions further cause the computer to:

receive a selection of a code editor;

receive an entry of software code to create a second function;

receive a selection describing a combination of the data analysis function and the second function; and

execute the second function in relation to the data analysis function in accordance with the described combination in order to perform a combined functionality of the data analysis function and the second function.

10. The non-transitory computer readable medium of claim 7 , wherein the instructions further cause the computer to:

receive a selection of a visualization function;

receive a selection describing a combination of the data analysis function and the visualization function; and

execute the visualization function in relation to the data analysis function in accordance with the described combination to display a result of the data analysis function.

11. The non-transitory computer readable medium of claim 7 , wherein the instructions further cause the computer to:

receive a selection of a report function;

receive a selection describing a combination of the data analysis function and the report function; and

execute the report function in relation to the data analysis function in accordance with the described combination to generate a report describing a result of the data analysis function.

12. The non-transitory computer readable medium of claim 7 , wherein the back-end data sets include retail-specific data that is at least one of cleansed retail data, and aggregate retail data.

13. The non-transitory computer readable medium of claim 7 , wherein the data analysis function is a machine learning algorithm.

14. A computing system comprising:

a processor;

a memory operably connected to the processor;

a non-transitory computer-readable medium operably connected to the processor and memory and storing computer-executable instructions that when executed by at least a processor of a computer cause the computer to:

generate and display a graphical user interface including one or more selectable generic options;

receive a selection of a data analysis function from among the selectable generic options;

receive user selections that assemble an application in an application window of the graphical user interface, wherein the application is assembled to create a hybrid approach to extract product attributes that combines both image and text description, and wherein the application includes the selected data analysis functions;

translate the selected data analysis function into pre-configured commands for a plurality of back-end tools for performing the selected data analysis function based on a mapping between the selected function and the pre-configured commands, wherein the pre-configured commands identify and access specific schema with a compatible format for reading the specific schema from each of the plurality of back end-tools to expose retail-specific back-end data sets through synonyms for fields of the back-end data sets;

execute the preconfigured commands to create the synonyms for retrieving corresponding retail-specific data from the plurality of the back-end tools;

execute the selected data analysis function on the synonyms for the fields of the retail-specific back-end data sets from the plurality of back-end tools and generate a data analysis result; and

create a restful service definition for the data analysis result that shares the data analysis result to other processes.

15. The computing system of claim 14 , wherein the retail-specific back-end data sets includes cleansed retail data.

16. The computer implemented method of claim 1 , further comprising receiving user selections that assemble an application to predict whether a customer is likely to churn in the application window of the graphical user interface, wherein the application includes the data analysis function.

17. The non-transitory computer readable medium of claim 7 , wherein the instructions further cause the computer to receive user selections that assemble an application to create a hybrid approach to extract product attributes that combines both image and text description in the application window of the graphical user interface.

18. The computer implemented method of claim 1 , further comprising receiving user selections that assemble an application to display affinities between products in a basket as a graph in the application window of the graphical user interface.

19. The computer implemented method of claim 1 , further comprising receiving user selections that assemble an application to produce a multiple time-step sales forecast in the application window of the graphical user interface, wherein the application includes the data analysis function.

20. The computer implemented method of claim 1 , further comprising receiving user selections that assemble an application to ingest customer clickstream information and identify clickstreams that indicate high-value customers in the application window of the graphical user interface, wherein the application includes the data analysis function.