Oracle Financial Services Software Limited

Oracle International Corporation

Rajaram Narasimha Vadapandeshwara

Tara Nandakishore Kant

Gangadhar Nagulakonda

Charles Rajkumar

Suresh Singh

Jesna Jacob

Pramit Dey

Bhargava Srinivasa

Seema M Monteiro

Subramanian Ramakrishnan

Shilpa Satheesh

Manmay Sethi

Farsana K

Bhargava S

Manu Goyal

Rony Joshy

Renjith Ravindran

Rekha Patil

Nagesh Shetty

Systems, methods, and other embodiments associated with associated with automatic two-way generation and synchronization of notebook and pipeline are described. In one embodiment, a computer-implemented method includes: identifying a difference between pipeline and notebook representations of application logic, wherein the difference is one of (i) a notebook paragraph without a corresponding pipeline node and (ii) a pipeline node without a corresponding notebook paragraph; synchronizing the pipeline representation and notebook representation by, for the notebook paragraph that does not have a corresponding pipeline node, automatically generating a new pipeline node in the pipeline representation, and for the pipeline node that does not have a corresponding notebook paragraph, automatically generating a new notebook paragraph in the notebook representation; and updating either a pipeline user interface to show the new pipeline node or a notebook user interface to show the new notebook paragraph.

Automatic two-way generation and synchronization of notebook and pipeline

Systems, methods, and other embodiments associated with associated with unified pipeline flow with common and phase-specific paths are described. In one embodiment, a method includes accepting, through a graphical user interface, a setting of a phase-specific link type for a link between nodes of a pipeline, wherein the phase-specific link type indicates that the link is associated with a particular phase; accepting, through the graphical user interface, a selection to execute the pipeline for the phase; parsing the pipeline to determine an execution set of nodes for execution in the phase based on the nodes being connected with links having either the link type or a default link type common to all phases; and executing the pipeline for the phase by executing the execution set of nodes, and not executing nodes not included in the set of nodes.

Unified pipeline flow with common and phase-specific paths

Techniques are disclosed for creating a workspace. A data processing system receives a request to create a workspace to implement a portion of a model deployed in a production environment. One or more data objects and associated metadata thereof relevant to the portion of the model, and an execution venue for the workspace are obtained. A set of instructions is generated for executing the one or more data objects and the associated metadata in the workspace. The workspace is created within the execution venue by instantiating the portion of the model, the one or more data objects, and the associated metadata in the workspace. The portion of the model in the workspace is processed using the one or more data objects and the associated metadata in accordance with the set of instructions, and the production environment is updated by the data processing system based on the processing.

Materialization of an analytical workspace

Systems, methods, and other embodiments associated with controlling an execution pipeline are described. In one embodiment, a method includes generating an execution pipeline for executing a plurality of tasks. The example method may also include evaluating execution definitions of the tasks to identify execution properties of the plurality of tasks. The example method may also include assigning each task to an execution environment selected from a set of execution environments based upon execution properties of the task matching execution properties of the execution environments. The example method may also include controlling the execution pipeline to execute each task within the assigned execution environments.

Computerized control of execution pipelines

Techniques for automatically deploying a version of a compute, both rule based and model based, with its dependencies when approved for deployment using one or more governance processes. One technique includes generating a compute fitting defined requirements and capable of executing on a defined model objective, generating a deployable archive bundle of the compute with dependencies based on a record of a lineage of the logical building blocks in dependency, analyzing performance of the compute with respect to a production compute deployed within a production environment, determining the performance of the compute is superior to the performance of the production compute based on the analyzing, and replacing the production compute in the production environment with the compute using the deployable archive bundle to facilitate deployment.

Production compute deployment and governance

Techniques are disclosed for attribution analysis in analytical workflows. A data processing system (DPS) obtains an overall model comprising one or more sub-models. The DPS selects an output variable of the overall model for which attribution of changes is to be performed, and a plurality of input variables against which changes are to be attributed to. The overall model is initially executed with respect to a data set of values for the plurality of input variables to generate a base result for the output variable. The overall model is iteratively executed based on a condition associated with the plurality of input variables to obtain a new result for the output variable. In each iteration, a value of an input variable is changed with respect to the data set of values and a change in the output variable with respect to the base result is attributed to the corresponding input variable.

Pipeline modeler supporting attribution analysis

Techniques for retaining in-memory dataframes beyond an in-memory processing session. One technique includes receiving a request to execute a first run having a first set of tasks, creating a first session to execute the first run, and executing the first run in the first session using a dataframe constructed for a dataset defined as a component of the first run. The executing the first run generates an updated dataframe. The technique further includes receiving a request to execute a second run having a second set of tasks. A dependency exists between the first run and the second run based on a condition that the dataset is defined as a component of the first run and the second run. The technique further includes creating a second session to execute the second run, and executing the second run in the second session using the updated dataframe for the dataset.

Re-using data structures beyond the life of an in-memory processing session

An aspect of the present disclosure generates instruction sets implementing business rules designed to update business objects of financial applications. In one embodiment, business rules designed to update business objects used by a financial application are processed to form a set of buckets (of rules) such that each bucket contains rules that do not have inter-dependency in execution order. Then, for each bucket, subsets of rules designed to update a common business object are determined, and a corresponding single instruction set is generated for each determined subset of rules. The instruction sets generated for the subsets of rules contained in each bucket are then executed concurrently.

Generating instruction sets implementing business rules designed to update business objects of financial applications

Control migration of a state machine using a dependency graph interface by: analyzing a state machine to determine objects and dependencies between the objects; generating a dependency graph that represents the objects and the dependencies between the objects, wherein the objects are represented by selectable icons; displaying the dependency graph on a display device; in response to a selection of a particular selectable icon, providing a migration option for an object represented by the selectable icon, wherein the migration option includes at least a selection between either a deep copy or a shallow copy for the object represented by the selectable icon; accepting and storing a selection of the migration option for the object represented by the particular selectable icon; and migrating the state machine to a target environment based at least in part on performing the migration option for the object represented by the particular selectable icon.

Dependency graph-controlled object and compute pipeline migration

An aspect of the present disclosure facilitates controlling access to objects having attributes defined against hierarchically organized domains, with each domain containing a corresponding fixed number of values. In one embodiment, in response to receiving data indicating specific hierarchies of the hierarchically organized domains, the corresponding fixed number of values of the corresponding domains in each hierarchy is displayed. Accordingly, a user is enabled to select a desired set of values from the corresponding fixed number of values of the corresponding domains, and to specify a security rule for a combination of the selected set of values and a user entity. The security rule is thereafter enforced when objects having attributes matching the selected set of values are accessed by the user entity.

Access control for objects having attributes defined against hierarchically organized domains containing fixed number of values

Systems, methods, and other embodiments associated with defining and executing a process within a single runtime environment are described. In one embodiment, a method includes executing a definition interface in the runtime environment for defining the process. The example method may also include receiving input of a process definition of the process through the definition interface and storing the process definition into a data structure. The example method may also include generating and displaying a selection interface populated with a plurality of execution types such as a workflow, a batch execution job, an analytical pipeline, and an interactive application interface. The example method may also include receiving a selected execution type through the selection interface and executing the process using the process definition that is transformed during execution to be compatible with the selected execution type. An execution interface, populated with process execution information, is executed in the runtime environment.

Interface and runtime environment for process definition and process execution tracking

Systems, methods, and other embodiments associated with introducing a new data structure to an executing application are described. In one embodiment, a method includes executing an application as an executing application to process data of a data structure maintained according to a data model. The example method may also include receiving a new data structure definition of a new data structure to define for the data model. The example method may also include performing impact analysis to determine whether the executing application is capable of processing data of the new data structure. The example method may also include updating the data model to include the new data structure definition to create an updated data model. The example method may also include generating control instructions to instruct the executing application to utilize data from the new data structure according to the updated data model.

Computer system and method for executing applications with new data structures

An aspect of the present disclosure facilitates application process defined using application objects to operate based on structured and unstructured data stores. In one embodiment, a mapping is maintained indicating the data objects defined according to an application data model that are respectively stored in a structured data store and an unstructured data store. Upon receiving an application object (of an application process) specifying an operation based on a data object according to the application data model, the mapping is examined to identify a specific data store storing the data corresponding to the data object. The operation is then translated to a set of instructions consistent with the interface requirements of the identified specific data store. The set of instructions are then executed on the specific data store to cause the operation to be performed based on the data object stored in the specific data store.

Growing community of inventors

Bengaluru, India

Rajaram Narasimha Vadapandeshwara