[1] This is a non data-agnostic method, as it uses a specified file type, downloaded from a specific location, and does not function unless those requirements are met.
[2][3][4][5] Data agnostic devices and programs work to solve these problems in a variety of ways.
Devices and programs[6] can become more data-agnostic by using a generic storage format to create, read, update and delete files.
Once you have your data saved in a generic storage format, this source can act as an entity synchronization layer.
Multiple devices and programs can create, read, update and delete (CRUD) the same information from the same storage location without formatting errors.
When multiple programs are accessing the same records, they may have different defined fields for the same type of concept.
This acts as a compatibility layer, as TSQL statements can retrieve, update, sort, and write data regardless of the format employed.
Since only one piece of code is being used for CRUD operations (regardless of the type of concept), there is a single point of failure.
While this improves the speed, it adds a non-data agnostic element to the process; however, it can be created easily through code generation.