Onetrust, LLC

Subramanian Viswanathan

Kevin Jones

Jonathan Blake Brannon

Milap Shah

Saravanan Pitchaimani

Dylan D Patton-Kuhl

Anand Balasubramanian

Ramana Malladi

Kabir A Barday

Jason L Sabourin

Casey Hill

Patrick Whitney

Mithun Babu

Jeffrey Baucom

Madhusudhan Kunhambu

Rajneesh Kesavan

Brian Kelly

Sathish Gopalakrishnan

Mohamed Kabad

Jayamohan Puthenveetil

Haribalan Raghupathy

Mahesh Sivan

Matthew Hennig

Aadil Allidina

Santosh Kumar Koti

Jonathan Lynn

Rahul Shinde

Zara Dana

Sivanandame Chandramohan

Abhishek Upadhyay

Nicholas Ian Pavlichek

Bryan Patrick Kveen

Eliza Rose Crawford

Ravi Bhattiprolu

Tianchen Cai

Arun Suresh

Santhosh Kumar Koti

Methods, systems, and non-transitory computer readable storage media are disclosed for dynamically generating and modifying interactive graph-based taxonomies associated with data processes in various domains. The disclosed system generates node data objects representing a domain-category hierarchy in connection with one or more computing data processes via a library of tools. The disclosed systems generates an attribute data object corresponding to an attribute assigned to a node data object in the graph-based taxonomy and links the attribute data object to node data objects according to parent/child relationships of the hierarchy. The disclosed system utilizes the parent/child relationships of the node data objects and attribute data object to aggregate attribute values of the attributes according to one or more aggregation operations. The disclosed systems provide indications of the aggregated attribute values for display via a graphical user interface for use in performing data processes.

Generating graph-based taxonomies via graphical user interface tools for generating representative data objects and customizing attributes

Methods, systems, and non-transitory computer readable storage media are disclosed for optimizing computer memory usage for lookup lists in computer memory via probabilistic data structures. For example, the disclosed system generates a probabilistic data structure (e.g., a Bloom filter) to represent data in a lookup list including multi-token items by hashing items of the lookup list to sets of bit values in a bit vector. The disclosed system classifies text content in a digital document by utilizing a maximum number of tokens from multi-token items in the lookup list to select and compare sets of sequential tokens in the digital document to the probabilistic data structure. The disclosed system also iteratively reduces the number of tokens in sets of sequential tokens for subsequent comparisons. Furthermore, in some aspects, the disclosed system causes a computing device to modify a digital document and/or database operations based on the classifications.

Generating probabilistic data structures for lookup tables in computer memory for multi-token searching

Various embodiments provide methods, apparatus, systems, computing devices, computing entities, and/or the like for identifying targeted data for a data subject across a plurality of data objects in a data source. In accordance with one embodiment, a method is provided comprising: receiving a request to identify targeted data for a data subject; identifying a first data object using metadata for a data source that identifies the first data object as associated with a first targeted data type for a data portion from the request; identifying a first data field from a graph data structure of the first data object that identifies the first data field as used for storing data having the first targeted data type; and querying the first data object based on the first data field and the data for the first targeted data type to identify a first targeted data portion for the data subject.

Systems and methods for targeted data discovery

Data processing systems and methods, according to various embodiments, are adapted for determining a categorization for each tracking tool that executes on a particular webpage based on a variety of criteria, such as the purpose of the tracking tool and its source script. The system may compare the characteristics of tracking tools on a webpage to a database of known tracking tools to determine the appropriate categorization. When a user visits the webpage, the system analyzes these categories and determines whether the tracking tool should be permitted to run based on the categories and/or other criteria, such as whether the user has consented to the use of that type of tracking tool.

Data processing systems and methods for automatically blocking the use of tracking tools

Aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for identifying data processing activities associated with various data assets based on data discovery results. In accordance various aspects, a method is provided comprising: identifying and scanning data assets to detect a subset of the data assets, wherein each asset of the subset is associated with a particular data element used for target data; generating a prediction for each pair of data assets of the subset on the target data flowing between the pair; identifying a data flow for the target data based on the prediction generated for each pair; and identifying a data processing activity associated with handling the target data based on a correlation identified for the particular data element, the subset, and/or the data flow with a known data element, subset, and/or data flow for the data processing activity.

Systems and methods for identifying data processing activities based on data discovery results

In general, various aspects provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for performing data discovery on a target computing system. In various aspects, a third party computing connects, via a public data network, to an edge node of the target computing system and instructs the target computing system to execute jobs to discover target data stored in data repositories in a private data network in the target computing system. In some aspects, the third party computing system may schedule the jobs on the target computing system based on computing resource availability on the target computing system.

Systems and methods for discovery, classification, and indexing of data in a native computing system

In general, various aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for generating and managing custom workflows for domain objects defined within microservices. In accordance with various aspects, a method is that comprises: receiving an attribute value for a custom workflow to include in a microservice that corresponds to an attribute defined for a workflow component; accessing mapping data for an attribute; identifying, based on the mapping data, a corresponding field of a workflows table mapped to the attribute; storing a record in the workflows table for the custom workflow with the attribute value stored in the corresponding field for the record to persist the custom workflow in the microservice.

Managing custom workflows for domain objects defined within microservices

In general, various aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for integrating third party computing system functionality into a first party computing system by providing a risk management and mitigation computing system configured to analyze a risk of integrating the functionality provided by the third party computing system and facilitating implementation of one or more data-related controls that include performing computer-specific operations to mitigate and/or eliminate the identified risks. For example, the risk management and mitigation computing system can access risk data in tenant computing systems to determine a risk score related to the integration of the third party computing system functionality based on risks determined during prior integrations of the third party computing system functionality by other tenant computing systems. The risk management and mitigation computing system can generate a recommended control when integrating the third party computing system functionality.

Systems and methods for mitigating risks of third-party computing system functionality integration into a first-party computing system

In general, various aspects of the present invention provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for generating and managing custom attributes and corresponding values for domain objects defined within microservices. In accordance with various aspects, a method is provided that comprises: receiving a custom attribute request for a domain object defined in a microservice that comprises a domain object identifier, a custom attribute to add to the domain object, and a value type for the custom attribute; identifying, based on the domain object identifier and the value type, a custom value table for the domain object that comprises placeholder fields; identifying a placeholder field that is available in the custom value table; and storing a record in the attribute schema table for the domain object and the custom attribute comprising mapping data that maps the custom attribute to the placeholder field for the custom value table.

Managing custom attributes for domain objects defined within microservices

Growing community of inventors

Marietta, GA, United States of America

Subramanian Viswanathan