Abstract: The present disclosure is directed to a reference voltage calibration. An apparatus includes a memory and a memory controller including a calibration circuit configured to perform a reference voltage calibration to determine a reference voltage used to distinguish between logic values read from the memory. The reference voltage calibration comprises performing horizontal calibrations at different reference voltage values to determine a range of delay values applied to a data strobe signal at which valid data is read from the memory. The calibration includes determining scores corresponding to ones of the plurality of horizontal calibrations in which a score for a particular one of the plurality of horizontal calibrations is based on a corresponding range of delay values and a reference voltage margin. Thereafter, the calibration circuit selects a calibrated reference voltage based on the scores corresponding to ones of the plurality of horizontal calibrations.

Abstract: 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.

Abstract: A memory subsystem and method for performing calibrations therein is disclosed. A memory subsystem includes a memory controller coupled to a memory by a plurality of signal paths. The memory controller is configured to perform an initial calibration to determine respective eye patterns corresponding to the ones of the plurality of signal paths. For a subsequent calibration, updated eye patterns are determined for a subset of the plurality of signal paths. Remaining ones of the plurality of signal paths (not included in the subset), are not active during the subsequent calibrations. Updated eye patterns for the remaining ones of the plurality of signal paths are determined based on information obtained during the initial calibration and information from signal paths in the subset designated proxies for the remaining ones of the plurality of signal paths.

Abstract: 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.

Abstract: 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.

Abstract: A memory subsystem and method for performing calibrations therein is disclosed. A memory subsystem includes a memory controller coupled to a memory by a plurality of signal paths. The memory controller is configured to perform an initial calibration to determine respective eye patterns corresponding to the ones of the plurality of signal paths. For a subsequent calibrations, updated eye patterns are determined for a subset of the plurality of signal paths. Remaining ones of the plurality of signal paths (not included in the subset), are not active during the subsequent calibrations. Updated eye patterns for the remaining ones of the plurality of signal paths are determined based on information obtained during the initial calibration and information from signal paths in the subset designated proxies for the remaining ones of the plurality of signal paths.

Abstract: 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.

Abstract: 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.

Abstract: A method and apparatus for selective reference voltage calibration in a memory subsystem is disclosed. A memory subsystem includes a memory coupled to a memory controller. The memory controller may operate in one of a number of different performance states. The memory controller further includes a calibration circuit configured to perform reference voltage calibrations for the various ones of the performance states to determine corresponding reference voltages. For a performance state change from an initial performance state to a final performance state, via an intermediate performance state, the memory controller is configured to transition to the intermediate performance state without causing the calibration circuit to perform a reference voltage calibration in that state. Thereafter, the memory controller transitions to the final performance state.

Abstract: 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.

Abstract: A method and apparatus for selective reference voltage calibration in a memory subsystem is disclosed. A memory subsystem includes a memory coupled to a memory controller. The memory controller may operate in one of a number of different performance states. The memory controller further includes a calibration circuit configured to perform reference voltage calibrations for the various ones of the performance states to determine corresponding reference voltages. For a performance state change from an initial performance state to a final performance state, via an intermediate performance state, the memory controller is configured to transition to the intermediate performance state without causing the calibration circuit to perform a reference voltage calibration in that state. Thereafter, the memory controller transitions to the final performance state.

Abstract: 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.

Abstract: A memory subsystem and method for performing calibrations therein is disclosed. A memory subsystem includes a memory controller coupled to a memory by a plurality of signal paths. The memory controller is configured to perform an initial calibration to determine respective eye patterns corresponding to the ones of the plurality of signal paths. For a subsequent calibrations, updated eye patterns are determined for a subset of the plurality of signal paths. Remaining ones of the plurality of signal paths (not included in the subset), are not active during the subsequent calibrations. Updated eye patterns for the remaining ones of the plurality of signal paths are determined based on information obtained during the initial calibration and information from signal paths in the subset designated proxies for the remaining ones of the plurality of signal paths.

Abstract: 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.

Abstract: 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.

Abstract: A memory subsystem and method for performing calibrations therein is disclosed. A memory subsystem includes a memory controller coupled to a memory by a plurality of signal paths. The memory controller is configured to perform an initial calibration to determine respective eye patterns corresponding to the ones of the plurality of signal paths. For a subsequent calibrations, updated eye patterns are determined for a subset of the plurality of signal paths. Remaining ones of the plurality of signal paths (not included in the subset), are not active during the subsequent calibrations. Updated eye patterns for the remaining ones of the plurality of signal paths are determined based on information obtained during the initial calibration and information from signal paths in the subset designated proxies for the remaining ones of the plurality of signal paths.

Abstract: Examples described herein include systems and methods for providing privacy information to a user of a user device. An example method can include detecting, at a management server, access of the private data by an entity other than the user, such as an administrator who is authorized to access the management server. The method further includes generating an event reflecting the access of the private data. The generated event can be stored as part of an event log in a database. The method further includes providing the event to the user device for display to the user. The event displayed on the user device can include information such as an identity of the accessing entity, a description of the private data that was accessed, and when the access occurred. The user can select a displayed event at the user device and request further information on the event from an administrator.

Abstract: Examples described herein include systems and methods for providing privacy information to a user of a user device. An example method can include detecting, at a management server, access of the private data by an entity other than the user, such as an administrator who is authorized to access the management server. The method further includes generating an event reflecting the access of the private data. The generated event can be stored as part of an event log in a database. The method further includes providing the event to the user device for display to the user. The event displayed on the user device can include information such as an identity of the accessing entity, a description of the private data that was accessed, and when the access occurred. The user can select a displayed event at the user device and request further information on the event from an administrator.

Abstract: Systems herein allow an administrator to efficiently set up user devices for use in a classroom environment. A management server can display a graphical user interface that includes selection options for defining and using carts of user devices. The carts can be selected and assigned to classes. The GUI also allows the administrator to specify which applications a class will use. Based on these selections, the management server can then manage which user devices install which applications, and allocate licenses accordingly.

Abstract: Systems herein allow an administrator to efficiently set up user devices for use in a classroom environment. A management server can display a graphical user interface that includes selection options for defining and using carts of user devices. The carts can be selected and assigned to classes. The GUI also allows the administrator to specify which applications a class will use. Based on these selections, the management server can then manage which user devices install which applications, and allocate licenses accordingly.