Distributed computing system with a synthetic data as a service asset assembly engine

One or more computer-readable media storing instructions thereon for implementing a distributed computing system asset assembly engine, which, when executed by one or more processors of a computing device cause the computing device to perform actions comprising:

• receiving a first source asset from a first distributed Synthetic Data as a Service (SDaaS) upload interface of a synthetic data as a service (SDaaS) integrated development environment (IDE) associated with both SDaaS distributed computing service operations and SDaaS machine-learning training service operations that are part of a service-oriented architecture of an SDaaS service, wherein the service-oriented architecture abstracts underlying the SDaaS distributed computing service operations that are managed via the SDaaS service from the SDaaS machine-learning training service operations to provide machine-learning training services using the distributed computing system asset assembly engine;
• receiving a second source asset from a second distributed SDaaS upload interface;
• ingesting the first source asset and the second source asset, wherein ingesting a source asset comprises automatically computing values for asset-variation parameters of the source asset, wherein the asset-variation parameters are programmable for machine-learning;
• generating a first synthetic data asset comprising a first set of values for the asset-variation parameters;
• generating a second synthetic data asset comprising a second set of values for the asset-variation parameters;
• and
• storing the first synthetic data asset and the second synthetic data asset in a synthetic data asset store.

A computer-implemented method for implementing a distributed computing system asset assembly engine, the method comprising:

• receiving a source asset from a distributed Synthetic Data as a Service (SDaaS) upload interface of a synthetic data as a service (SDaaS) integrated development environment (IDE) associated with both SDaaS distributed computing service operations and SDaaS machine-learning training service operations that are part of a service-oriented architecture of an SDaaS service, wherein the service-oriented architecture abstracts underlying the SDaaS distributed computing service operations that are managed via the SDaaS service from the SDaaS machine-learning training service operations to provide machine-learning training services using the distributed computing system asset assembly engine;
• ingesting the source asset, wherein ingesting the source asset comprises automatically computing values for asset-variation parameters of the source asset, wherein the asset-variation parameters are programmable for machine-learning;
• and
• generating a synthetic data asset comprising the values for the asset-variation parameters.