Abstract: In particular embodiments, a data processing data inventory generation system is configured to: (1) generate a data model (e.g., a data inventory) for one or more data assets utilized by a particular organization; (2) generate a respective data inventory for each of the one or more data assets; and (3) map one or more relationships between one or more aspects of the data inventory, the one or more data assets, etc. within the data model. In particular embodiments, a data asset (e.g., data system, software application, etc.) may include any entity that collects, processes, contains, and/or transfers personal data (e.g., a software application, database, website, server, etc.). A data asset may include any software or device (e.g., server or servers) utilized by a particular entity for such data collection, processing, transfer, storage, etc. The system may then utilize the generated model to fulfil a data subject access request.

Abstract: In general, various aspects of the present disclosure provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for addressing a modified risk rating identifying a risk to an entity of having computer-implemented functionality provided by a vendor integrated with a computing system of the entity.

Abstract: A method, in various aspects, comprises: (1) receiving a query from a first party computing system related to integrating third party computing functionality into the first party computing system; (2) identifying a set of third party entities that provide the third party computing functionality; (3) accessing integration data; (4) identifying a set of reference entities, the set of reference entities including, for each respective third party entity, a respective reference entity that has previously integrated the third party computing into a respective reference entity computing system associated with the respective reference entity; (5) determining second integration data with respect to the set of reference entities integrating the third party computing functionality; (6) generating, based on the first integration data and the second integration data, data responsive to the query that is specific to the first party computing system; and (7) taking an action with respect to the data.

Abstract: Various Data Subject Access Request (DSAR) processing systems are adapted for presenting a first webform on a first web site, the first webform being adapted to receive DSAR's and to route the requests to a first designated individual for processing; presenting a second webform on a second web site, the second webform being adapted to receive DSAR's and to route the requests to a second designated individual for processing; receiving, via the first webform, a first DSAR; at least partially in response to the receiving the first DSAR, automatically routing the first DSAR to the first designated individual for handling; receiving, via the second webform, a second DSAR; at least partially in response to the receiving the second DSAR, automatically routing the second DSAR to the second designated individual for handling; and communicating a status of both the first DSAR and the second DSAR via a single user interface.

Abstract: Data processing systems and methods according to various embodiments are adapted for automatically detecting and documenting privacy-related aspects of computer software. Particular embodiments are adapted for: (1) automatically scanning source code to determine whether the source code include instructions for collecting personal data; and (2) facilitating the documentation of the portions of the code that collect the personal data. For example, the system may automatically prompt a user for comments regarding the code. The comments may be used, for example, to populate: (A) a privacy impact assessment; (B) system documentation; and/or (C) a privacy-related data map. The system may comprise, for example, a privacy comment plugin for use in conjunction with a code repository.

Abstract: Responding to a data subject access request includes receiving the request and identifying the requestor and source. In response to identifying the requestor and source, a computer processor determines whether the data subject access request is subject to fulfillment constraints, including whether the requestor or source is malicious. If so, then the computer processor denies the request or requests a processing fee prior to fulfillment. If not, then the computer processor fulfills the request.

Abstract: Methods, systems, and non-transitory computer readable storage media are disclosed for managing computing systems according to detect and correct configuration gaps with specific system requirements frameworks. Specifically, the disclosed system accesses a digital data repository to determine attribute values of data objects representing functions or infrastructure associated with handling target data for an entity. The disclosed system determines a digital representation of a system requirements framework that indicates controls associated with handling specific data types. Based on the attribute values and a gap rules set associated with the system requirements framework, the disclosed system determines configuration gaps to be addressed via control actions for installing controls in connection with various data assets or data processing operations.

Abstract: In particular embodiments, in response a data subject submitting a request to delete their personal data from an organization's systems, the system may: (1) automatically determine where the data subject's personal data is stored; (2) in response to determining the location of the data (which may be on multiple computing systems), automatically facilitate the deletion of the data subject's personal data from the various systems; and (3) determine a cause of the request to identify one or more processing activities or other sources that result in a high number of such requests.

Abstract: Data processing systems and methods according to various embodiments are adapted for automatically detecting and documenting privacy-related aspects of computer software. Particular embodiments are adapted for: (1) automatically scanning source code to determine whether the source code include instructions for collecting personal data; and (2) facilitating the documentation of the portions of the code that collect the personal data. For example, the system may automatically prompt a user for comments regarding the code. The comments may be used, for example, to populate: (A) a privacy impact assessment; (B) system documentation; and/or (C) a privacy-related data map. The system may comprise, for example, a privacy comment plugin for use in conjunction with a code repository.

Abstract: A privacy management system that is configured to process one or more data subject access requests and further configured to: (1) enable a data protection officer to submit an audit request; (2) perform an audit based on one or more parameters provided as part of the request (e.g., one or more parameters such as how long an average request takes to fulfill, one or more parameters related to logging and/or tracking data subject access requests and/or complaints from one or more particular customer advocacy groups, individuals, NGOs, etc.); and (3) provide one or more audit results to the officer (e.g., by displaying the results on a suitable display screen).

Abstract: In general, various aspects of the present disclosure provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for addressing a modified risk rating identifying a risk to an entity of having computer-implemented functionality provided by a vendor integrated with a computing system of the entity.

Abstract: Various aspects of the disclosure provide methods, apparatus, systems, computing devices, computing entities, and/or the like for facilitating the exchange of data among a diverse group of first and third party computing environments. Accordingly, various aspects of the disclosure provide a data exchange computing platform that facilitates data exchange among a diverse group of first and third party computing environments. In some aspects, the data exchange computing platform provides a data exchange service available to various first and third parties who wish to exchange data.

Abstract: In general, various aspects of the present disclosure provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for addressing a modified risk rating identifying a risk to an entity of having computer-implemented functionality provided by a vendor integrated with a computing system of the entity.

Abstract: In particular embodiments, a data processing data inventory generation system is configured to: (1) generate a data model (e.g., a data inventory) for one or more data assets utilized by a particular organization; (2) generate a respective data inventory for each of the one or more data assets; and (3) map one or more relationships between one or more aspects of the data inventory, the one or more data assets, etc. within the data model. In particular embodiments, a data asset (e.g., data system, software application, etc.) may include, for example, any entity that collects, processes, contains, and/or transfers personal data (e.g., such as a software application, “internet of things” computerized device, database, website, data-center, server, etc.). The system may be configured to identify particular data assets and/or personal data in data repositories using any suitable intelligent identity scanning technique.

Abstract: In particular embodiments, a data processing data inventory generation system is configured to: (1) generate a data model (e.g., a data inventory) for one or more data assets utilized by a particular organization; (2) generate a respective data inventory for each of the one or more data assets; and (3) map one or more relationships between one or more aspects of the data inventory, the one or more data assets, etc. within the data model. In particular embodiments, a data asset (e.g., data system, software application, etc.) may include, for example, any entity that collects, processes, contains, and/or transfers personal data (e.g., such as a software application, “internet of things” computerized device, database, website, data-center, server, etc.). For example, a first data asset may include any software or device (e.g., server or servers) utilized by a particular entity for such data collection, processing, transfer, storage, etc.

Abstract: In general, various aspects of the present disclosure provide methods, apparatuses, systems, computing devices, computing entities, and/or the like for addressing a modified risk rating identifying a risk to an entity of having computer-implemented functionality provided by a vendor integrated with a computing system of the entity.

Abstract: A Data Subject Access Request (DSAR) Prioritization System, according to various embodiments, is adapted for (1) executing the steps of receiving a data subject access request (DSAR); (2) at least partially in response to receiving the DSAR, obtaining metadata associated with at least one of the DSAR or a data subject associated with the DSAR; (3) using the metadata to determine whether a priority of the DSAR should be adjusted based at least in part on the obtained metadata; and (4) in response to determining that the priority of the DSAR should be adjusted based at least in part on the obtained metadata, adjusting the priority of the DSAR.

Abstract: In various embodiments, a data map generation system is configured to receive a request to generate a privacy-related data map for particular computer code, and, at least partially in response to the request, determine a location of the particular computer code, automatically obtain the particular computer code based on the determined location, and analyze the particular computer code to determine privacy-related attributes of the particular computer code, where the privacy-related attributes indicate types of personal information that the particular computer code collects or accesses. The system may be further configured to generate and display a data map of the privacy-related attributes to a user.

Abstract: In particular embodiments, a data subject request processing system may be configured to utilize one or more local storage nodes in order to process a data subject access request on behalf of a data subject. In particular embodiments, the one or more local storage nodes may be local to the data subject making the request (e.g., in the same country as the data subject, in the same jurisdiction, in the same geographic area, etc.). The system may, for example, be configured to: (1) receive a data subject access request from a data subject (e.g., via a web form); (2) identify a suitable local storage node based at least in part on the request and/or the data subject; (3) route the data subject access request to the identified local storage node; and (4) process the data subject access request at the identified local storage node.

Abstract: Data processing systems and methods, according to various embodiments, are adapted for automatically assessing the level of security and/or privacy risk associated with doing business with a particular vendor or other entity and for generating training material for such vendors. In various embodiments, the systems may automatically obtain and use any suitable information to assess such risk levels including, for example: (1) any security and/or privacy certifications held by the vendor; (2) the terms of one or more contracts between a particular entity and the vendor; (3) the results of one or more privacy impact assessments for the vendor; and/or (4) any other suitable data. The system may be configured to automatically approve or reject a particular vendor based on the assessed risk level associated with the vendor and this information may be automatically communicated to an entity considering doing business with the vendor and/or the vendor itself.