Accenture Global Solutions Limited

Stmicroelectronics International N.v.

Abhishek Datta Sharma

Jayanthi Mohanram

Madhura Shivaram

Prateek Shah

Mani Gupta

Baljit Malhotra

Deepika Bhaskar

Chung-Sheng Li

Vivek Shyamlal Sharma

Deepak Kumar

Guruprasad Dasappa

Suraj Govind Jadhav

Arvind Maheswaran

Suresh Venkatasubramaniyan

Anil Vohra

Kaushal Mody

Himani Shukla

Srikrishna Raamadhurai

Arun Srinivasan

Amol Deshpande

Siddhartha Asthana

Kapil Kumar Gupta

Prasanna Kulkarni

Rohit Anand

Ravikumar Setty

Varsha Ajit Shrikhande

Kamal Bablani

Ankit Khurana

Priyanka Niranjan

Supriya Sahoo

Palaniappan Ganesh Kumar

Ragavendran Ramesh

A system for providing performance optimization for a software solution may scan multiple predefined levels of the software solution to extract corresponding metadata information from each of the multiple predefined levels. The system may store the extracted corresponding metadata information pertaining to standard parameters associated with performance of the software solution. The system may determine a standard score based on a plurality of attributes of the extracted corresponding metadata information, optimize the determined standard score based on training data received from a learning model, and generate an insight information comprising information related to determined rule violations and of evaluation steps involved in determining the determined standard score.

System performance optimization

In some implementations, a device may receive extensibility data related to one or more custom code objects installed in a current environment. The device may classify the one or more custom code objects in one or more respective categories and determine one or more respective complexities associated with the one or more custom code objects based on the extensibility data. The device may generate an extensibility recommendation for deploying the one or more custom code objects to a target environment based on the one or more respective categories and the one or more respective complexities associated with the one or more custom code objects. The extensibility recommendation may be generated based on the one or more custom code objects satisfying extensibility conditions associated with the target environment. The device may provide an output relating to the extensibility recommendation.

Extensibility recommendation system for custom code objects

A device may receive source data identifying source enterprise software and may process the source data to determine field mapping data. The device may process the source data, with a first model, to determine implementation guide data identifying implementation guides, and the device may convert data configurations from the source data to target data configurations. The device may generate transport request management data for the target enterprise software based on the source data and the implementation guide data and may process the source data and the implementation guide data, with a second model, to determine copy functionality data identifying functionality of the source enterprise software to be copied. The device may process the source data, with a third model, to determine consolidation data identifying the source data to be consolidated and may configure the target enterprise software, based on the determined data, to generate configured target enterprise software.

Utilizing models for replacing existing enterprise software with new enterprise software

A device may receive information associated with an entity. The information may include a first resource and a second resource. The first resource may be associated with a first file type, and the second resource may be associated with a second file type that is different than the first file type. The first resource may be associated with a first source, and the second resource may be associated with a second source that is different than the first source. The device may extract a plurality of attributes associated with the entity based on the information. The device may implement a natural language processing technique to extract the plurality of attributes. The device may associate the plurality of attributes with a plurality of elements based on extracting the plurality of attributes. The device may provide information that identifies the plurality of elements and the plurality of attributes to permit and/or cause an action to be performed.

Identifying attributes associated with an entity using natural language processing

A system for reconciliation comprises a determination engine to determine whether data is structured or unstructured, a data structuring engine to structure the data, and a rule extraction engine to determine relations between pairs of values of a first set and a second set of data. The system further comprises a matching engine to generate a confidence score for each pair of the values, a categorization engine to classify the pairs of values into matched pairs and unmatched pairs, a validation engine to validate matching and classification of the pairs based on a user feedback, and a learning engine to store details pertaining to the validation of the matching and the classification over a period of time. The learning engine forwards the details to the rule extraction engine and the categorization engine to determine the relations between subsequent pairs of values and classify the pairs based on the stored details.

Data reconciliation

A device may receive, from a user device, a request for a code assessment of a proposed change to an enterprise resource planning (ERP) system of an organization to identify an impact of implementing the proposed change on custom code associated with the ERP system. The device may obtain data identifying custom items associated with the custom code from a data structure associated with the ERP system. The device may generate custom code metadata for the custom items by performing error checks to determine whether the custom items will cause errors after the proposed change is implemented. The device may generate an assessment report for the code assessment by processing the custom code metadata. The device may provide the assessment report for display on an interface of the user device, and may perform actions to permit the proposed change to be implemented without the errors occurring.

Code assessment platform

In an embodiment are provided are a differential amplifier, a method of amplifying a differential input signal, a device including a differential amplifier, and a low voltage differential signaling receiver.

Differential amplifier

Growing community of inventors

Delhi, India

Abhishek Datta Sharma