Abstract: Described is a system (and method) that provides a framework for performing data transformations, which may be part of an Extract, Transform, and Load (ETL) process. The system may perform a data transformation by creating a pipeline that executes a set of independent software components (or component, plugins, add-ons, etc.). The components may be executed as individual services (e.g., microservices) that may be provided within containers to allow the components to be deployed as self-contained units on various types of host systems including cloud-based infrastructures. In addition, to provide further flexibility for the framework, the components may be implemented using preexisting software libraries.

Abstract: In some implementations, a device may receive an input for a first prediction model. The device may execute, using the input, the first prediction model to generate a set of outputs, wherein the set of outputs is based on a set of inputs to a data processing pipeline associated with the first prediction model. The device may generate using a simulation engine and based on the set of outputs of the first prediction, a set of simulations of a set of results of implementing a set of actions associated with the first prediction model, wherein the set of simulations is associated with a simulated dataset representing a set of forecasts for simulating the set of results of implementing the set of actions. The device may output the simulated dataset to a model generation pipeline.

Abstract: Described is a system (and method) that provides a framework for performing data transformations, which may be part of an Extract, Transform, and Load (ETL) process. The system may perform a data transformation by creating a pipeline that executes a set of independent software components (or component, plugins, add-ons, etc.). The components may be executed as individual services (e.g., microservices) that may be provided within containers to allow the components to be deployed as self-contained units on various types of host systems including cloud-based infrastructures. In addition, to provide further flexibility for the framework, the components may be implemented using preexisting software libraries.

Abstract: Described is a system (and method) that provides a framework for performing data transformations, which may be part of an Extract, Transform, and Load (ETL) process. The system may perform a data transformation by creating a pipeline that executes a set of independent software components (or component, plugins, add-ons, etc.). The components may be executed as individual services (e.g., microservices) that may be provided within containers to allow the components to be deployed as self-contained units on various types of host systems including cloud-based infrastructures. In addition, to provide further flexibility for the framework, the components may be implemented using preexisting software libraries.

Abstract: Described is a system (and method) that provides a framework for performing data transformations, which may be part of an Extract, Transform, and Load (ETL) process. The system may perform a data transformation by creating a pipeline that executes a set of independent software components (or component, plugins, add-ons, etc.). The components may be executed as individual services (e.g., microservices) that may be provided within containers to allow the components to be deployed as self-contained units on various types of host systems including cloud-based infrastructures. In addition, to provide further flexibility for the framework, the components may be implemented using preexisting software libraries.