Identifying associated data objects

1. A method for data processing, comprising:

receiving, at a first data management system associated with a content management system, an identifier of at least one content item;

generating a content object that includes one or more content fields corresponding to characteristics of the at least one content item, wherein a format of the content object corresponds to the format of data objects of a second data management system different from the first data management system, the data objects corresponding to products of an electronic commerce system associated with the second data management system, wherein the content object is generated to correspond to the format of a product of the electronic commerce system;

transmitting, via an application programming interface, the content object to a machine learning model that is configured to identify relationships between the data objects of the second data management system;

receiving, from the second data management system via the application programming interface, an indication of two or more data objects of the second data management system that are identified by the machine learning model as being related to the at least one content item of the first data management system; and

transmitting, to a plurality of user devices, the at least one content item that includes links to the two or more data objects identified by the machine learning model configured for the second data management system.

2. The method of claim 1 , further comprising:

receiving, from the second data management system, confidence scores for the two or more data objects or confidence scores for categories associated with the two or more data objects; and

filtering the two or more data objects or the associated categories based at least in part on the confidence scores.

3. The method of claim 1 , further comprising:

receiving, from a user of the first data management system, a selection of at least one data object of the two or more data objects from the second data management system or a selection of one or more categories associated with the at least one data object; and

linking the at least one data object to the at least one content item based at least in part on the selection.

4. The method of claim 1 , further comprising:

receiving an indication that at least one user device of the plurality of user devices interacted with the links to the two or more data objects included with the at least one content item.

5. The method of claim 1 , wherein the at least one content item comprises an image, a body of text, a product, a product description, a video, an advertisement, or a combination thereof.

6. The method of claim 1 , wherein the two or more data objects comprise serializable objects.

7. The method of claim 1 , wherein:

the one or more content fields corresponding to the characteristics of the at least one content item comprise a title, a description, images, and multimedia information associated with the at least one content item; and

the one or more content fields corresponding to the characteristics of the two or more data objects comprise an image attribute, a description attribute, and pricing information associated with the two or more data objects of the second data management system.

8. The method of claim 1 , further comprising:

receiving, at the first data management system, an indication of an updated version of the at least one content item; and

receiving, from the second data management system, an identifier for at least one data object that corresponds to the updated version of the at least one content item.

9. The method of claim 1 , further comprising:

identifying, at the second data management system, the two or more data objects based at least in part on using the machine learning model to process the content object, wherein processing the content object comprises cleaning the content object, converting the content object to the format of the data objects of the second data management system, and vectorizing the content object using a word embedding function.

10. The method of claim 1 , wherein generating the content object comprises:

generating the content object that corresponds to the format of a product object of the electronic commerce system that is the second data management system such that the machine learning model of the electronic commerce system compares the content object to product objects of the electronic commerce system to identify the relationships between the content object and the product objects.

11. An apparatus for data processing, comprising:

a processor,

memory coupled with the processor; and

instructions stored in the memory and executable by the processor to cause the apparatus to:

receive, at a first data management system associated with a content management system, an identifier of at least one content item;

generating a content object that includes one or more content fields corresponding to characteristics of the at least one content item, wherein a format of the content object corresponds to the format of data objects of a second data management system different from the first data management system, the data objects corresponding to products of an electronic commerce system associated with the second data management system, wherein the content object is generated to correspond to the format of a product of the electronic commerce system;

transmit, via an application programming interface, the content object to a machine learning model that is configured to identify relationships between the data objects of the second data management system;

receive, from the second data management system via the application programming interface, an indication of two or more data objects of the second data management system that are identified by the machine learning model as being related to the at least one content item of the first data management system; and

transmit, to a plurality of user devices, the at least one content item that includes links to the two or more data objects identified by the machine learning model configured for the second data management system.

12. The apparatus of claim 11 , wherein the instructions are further executable by the processor to cause the apparatus to:

receive, from the second data management system, confidence scores for the two or more data objects or confidence scores for categories associated with the two or more data objects; and

filter the two or more data objects or the associated categories based at least in part on the confidence scores.

13. The apparatus of claim 11 , wherein the instructions are further executable by the processor to cause the apparatus to:

receive, from a user of the first data management system, a selection of at least one data object of the two or more data objects from the second data management system or a selection of one or more categories associated with the at least one data object; and

link the at least one data object to the at least one content item based at least in part on the selection.

14. The apparatus of claim 11 , wherein the instructions are further executable by the processor to cause the apparatus to:

receive an indication that at least one user device of the plurality of user devices interacted with the links to the two or more data objects included with the at least one content item.

15. A non-transitory computer-readable medium storing code for data processing, the code comprising instructions executable by a processor to:

receive, at a first data management system associated with a content management system, an identifier of at least one content item;

generating a content object that includes one or more content fields corresponding to characteristics of the at least one content item, wherein a format of the content object corresponds to the format of data objects of a second data management system different from the first data management system, the data objects corresponding to products of an electronic commerce system associated with the second data management system, wherein the content object is generated to correspond to the format of a product of the electronic commerce system;

transmit, via an application programming interface, the content object to a machine learning model that is configured to identify relationships between the data objects of the second data management system;

receive, from the second data management system via the application programming interface, an indication of two or more data objects of the second data management system that are identified by the machine learning model as being related to the at least one content item of the first data management system; and

transmit, to a plurality of user devices, the at least one content item that includes links to the two or more data objects identified by the machine learning model configured for the second data management system.

16. The non-transitory computer-readable medium of claim 15 , wherein the instructions are further executable to:

receive, from the second data management system, confidence scores for the two or more data objects or confidence scores for categories associated with the two or more data objects; and

filter the two or more data objects or the associated categories based at least in part on the confidence scores.

17. The non-transitory computer-readable medium of claim 15 , wherein the instructions are further executable to:

receive, from a user of the first data management system, a selection of at least one data object of the two or more data objects from the second data management system or a selection of one or more categories associated with the at least one data object; and

link the at least one data object to the at least one content item based at least in part on the selection.