Microsoft Technology Licensing, LLC

Joyce Yu Cahoon

Avrilia Floratou

Vu Minh Le

Fang Liu

Vivek Gupta

Subramaniam Venkatraman Krishnan

Yiwen Zhu

Irene Rogan Shaffer

Ya Lin

Jordan Joseph Henkel

Sreraman Narasimhan

Ehimwenma Nosakhare

Andreas Christian Mueller

Haitao Song

Wee Hyong Tok

Dalitso Hansini Banda

Jason Wang

Neha Godwal

Shaily Jignesh Fozdar

Yan Qiu

Wenjing Wang

Neetu Singh

Raymond Truong

XingYu Liu

Maria Alexandra Ciortea

Pratyush Rawat

Abhishek Narain

Gust Verbruggen

Noelle Yanhui Li

David Joseph Donahue

Daniel Muñoz Huerta

Anja Gruenheid

Richard Anarfi

A computer-implemented method for performing natural language-based data integration includes causing execution of a data integration application on a remote device via a network and causing surfacing of a GUI corresponding to the data integration application on a display of the remote device. The method includes receiving, via the GUI, a natural language input representing a data integration task, generating, via an LLM, a set of ordered activities corresponding to the data integration task represented by the natural language input, and selecting, via the LLM, one or more APIs for performing each activity within the set of ordered activities. The method also includes generating a data pipeline based on the set of ordered activities and the API(s) for performing each activity, as well as back-translating the data pipeline to a desired data format for execution by the data integration application.

Natural language-based data integration

Methods, systems, apparatuses, and computer-readable storage mediums described herein are directed to determining and recommending an optimal compute resource configuration for a cloud-based resource (e.g., a server, a virtual machine, etc.) for migrating a customer to the cloud. The embodiments described herein utilize a statistically robust approach that makes recommendations that are more flexible (elastic) and account for the full distribution of the amount of resource usage. Such an approach is utilized to develop a personalized rank of relevant recommendations to a customer. To determine which compute resource configuration to recommend to the customer, the customer's usage profile is matched to a set of customers that have already migrated to the cloud. The compute resource configuration that reaches the performance most similar to the performance of the configurations utilized by customers in the matched set is recommended to the user.

Cloud-based compute resource configuration recommendation and allocation for database migration

Systems, methods, and devices are described for enabling a user to import a library into a computer program under development. The library includes a data storage interface, one or more semantic objects, and one or more data manipulation or data analysis operations. A user is able to reference code of the library within the computer program under development to generate a dataset from data obtained via the data storage interface and associate the one or more semantic objects with the dataset to generate a semantically-annotated dataset. Systems, methods, and devices enable, based on the importing: the user to invoke a semantic-guided operation of the library that utilizes the semantically-annotated dataset to infer an aspect of a data manipulation or data analysis operation to be performed on the semantically-annotated dataset; or the suggestion of a data manipulation or data analysis operation to the user based on the semantically-annotated dataset.

System and method for semantic aware data science

Growing community of inventors

Woodinville, WA, United States of America

Joyce Yu Cahoon