Wells Fargo Bank, N.a.

Salesforce, Inc.

Anand Nair

Ignacio Agustin Manzano

Manish Dutt Purohit

Saebom Kwon

Berkay Polat

Vijay Gopalakrishnan

Subhash Periasamy

Arvind K Radhakrishnen

Udayakumar Dhansingh

In the present disclosure, systems and methods are described for allowing a non-code user to create to transform a database in an ETL pipeline. Specifically, as disclosed herein, a user can take a database and receive a ruleset to apply to the database in an ETL pipeline. The data linting system may take the database and extract a schema and a data sample from it. Further, the data linting system may use the schema and data sample to create two rulesets. With these rulesets, the data linting system combines them to create a final ruleset which may be validated using the data sample. The data linting system then sends the final ruleset and the validation report to the user. With this system, the user only needs to give it a database and will receive a ruleset that is able to be immediately used in an ETL pipeline.

Automatic data linting rules for ETL pipelines

Techniques discussed herein describe an example system for verifying the identity and location of a customer in a bank branch parking lot. A server determines whether to provision a service for a vehicle based on telemetry data received from a telemetry module on the vehicle in a fleet of vehicles. The telemetry data includes a first location and status information of the vehicle. The server identifies a vendor to provide the service and directs the vehicle to a second location of the vendor from the first location of the vehicle. The server provides authorization to the vehicle for an on-board transaction module to initiate a request for the service when the vehicle is at the second location of the vendor.

Computer-based system for secure curbside banking

Growing community of inventors

San Francisco, CA, United States of America

Anand Nair