Abstract: According to some implementations, compliance assessment metrics in a subset of two or more compliance assessment metrics are combined to form a combined compliance assessment metric. Each compliance assessment metric in the subset reflects a level of compliance of a set of rules with a different type of data privacy and/or data security laws, regulations, and/or policy. The set of rules are to manage personal data in an organization instance of a customer of a cloud-based software provider capable of hosting the organization instance in one or more datacenters in a plurality of different geographic regions. An ability to move data from the organization instance from a first geographic region to a second geographic region is gated based on the combined compliance assessment metric. In addition, the combined compliance assessment metric is displayed as part of a data policy compliance service provided by the cloud-based software provider.

Abstract: According to some implementations, compliance assessment metrics in a subset of two or more compliance assessment metrics are combined to form a combined compliance assessment metric. Each compliance assessment metric in the subset reflects a level of compliance of a set of rules with a different type of data privacy and/or data security laws, regulations, and/or policy. The set of rules are to manage personal data in an organization instance of a customer of a cloud-based software provider capable of hosting the organization instance in one or more datacenters in a plurality of different geographic regions. In addition, a dashboard, which is part of a data policy compliance service provided by the cloud-based software provider, is caused to be displayed and includes at least the combined compliance assessment metric.

Abstract: According to some implementations, a data policy compliance service causes the display of a dashboard, wherein the dashboard identifies a first geographic region in which there is a datacenter hosting an organization instance of a customer of a cloud-based software provider. Responsive to user interaction, the data policy compliance service causes the display of the dashboard to reflect information regarding a possible migration of the organization instance from the first geographic region to a second geographic region of the plurality of geographic regions. The information includes a set of one or more compliance assessment metrics reflecting a level of compliance of the organization instance with data privacy and/or data security laws, regulations, and/or policy.

Abstract: According to some implementations, a data policy compliance service causes the display of a dashboard, wherein the dashboard identifies a first geographic region in which there is a datacenter hosting an organization instance of a customer of a cloud-based software provider. Responsive to user interaction, the data policy compliance service causes the display of the dashboard to reflect information regarding a possible migration of the organization instance from the first geographic region to a second geographic region of the plurality of geographic regions. The information includes a set of one or more compliance assessment metrics reflecting a level of compliance of the organization instance with data privacy and/or data security laws, regulations, and/or policy.

Abstract: According to some implementations, compliance assessment metrics in a subset of two or more compliance assessment metrics are combined to form a combined compliance assessment metric. Each compliance assessment metric in the subset reflects a level of compliance of a set of rules with a different type of data privacy and/or data security laws, regulations, and/or policy. The set of rules are to manage personal data in an organization instance of a customer of a cloud-based software provider capable of hosting the organization instance in one or more datacenters in a plurality of different geographic regions. In addition, a dashboard, which is part of a data policy compliance service provided by the cloud-based software provider, is caused to be displayed and includes at least the combined compliance assessment metric.

Abstract: The technology disclosed relates to processing events generated by Internet of Things (IoT) devices. In particular, it relates to storing a machine-readable declarative specification of stateful event processing of an automated multi-step progression of monitoring of Internet of Things (IoT) devices that generate events. It includes compiling into tangible memory, in response to the declarative specification, a state processing network that implements a multi-step progression of monitoring events generated by the IoT devices. The state processing network implements both the time based transition triggers and the event based transition triggers after being initiated by the IoT devices. Further, data structures, which record monitoring status of particular IoT devices, are compiled. Finally, the state processing network further selects an alternative action to trigger, and triggers the selected action using at least some data from a particular event being processed.

Abstract: The technology disclosed offers a declarative and visualization framework that implements a state machine for multi-step progression of interaction with an entity. The declarative framework is usable over and over for a broad range of applications because it provides a simple rule-based authoring tool that can be used for specifying different elements and components of a complex state machine, including state definitions, state transition triggers, state transition conditions and state transition actions. Once defined, the state machine is automatically generated and visually implemented based on the declarative input provided by a non-technical user.

Abstract: The technology disclosed relates to processing events generated by Internet of Things (IoT) devices. In particular, it relates to storing a machine-readable declarative specification of stateful event processing of an automated multi-step progression of monitoring of Internet of Things (IoT) devices that generate events. It includes compiling into tangible memory, in response to the declarative specification, a state processing network that implements a multi-step progression of monitoring events generated by the IoT devices. The state processing network implements both the time based transition triggers and the event based transition triggers after being initiated by the IoT devices. Further, data structures, which record monitoring status of particular IoT devices, are compiled. Finally, the state processing network further selects an alternative action to trigger, and triggers the selected action using at least some data from a particular event being processed.

Abstract: The technology disclosed relates to processing events generated by Internet of Things (IoT) devices. In particular, it relates to storing a machine-readable declarative specification of stateful event processing of an automated multi-step progression of monitoring of Internet of Things (IoT) devices that generate events. It includes compiling into tangible memory, in response to the declarative specification, a state processing network that implements a multi-step progression of monitoring events generated by the IoT devices. The state processing network implements both the time based transition triggers and the event based transition triggers after being initiated by the IoT devices. Further, data structures, which record monitoring status of particular IoT devices, are compiled. Finally, the state processing network further selects an alternative action to trigger, and triggers the selected action using at least some data from a particular event being processed.

Abstract: The technology disclosed offers a declarative and visualization framework that implements a state machine for multi-step progression of interaction with an entity. The declarative framework is usable over and over for a broad range of applications because it provides a simple rule-based authoring tool that can be used for specifying different elements and components of a complex state machine, including state definitions, state transition triggers, state transition conditions and state transition actions. Once defined, the state machine is automatically generated and visually implemented based on the declarative input provided by a non-technical user.

Abstract: The technology disclosed relates to processing events generated by Internet of Things (IoT) devices. In particular, it relates to storing a machine-readable declarative specification of stateful event processing of an automated multi-step progression of monitoring of Internet of Things (IoT) devices that generate events. It includes compiling into tangible memory, in response to the declarative specification, a state processing network that implements a multi-step progression of monitoring events generated by the IoT devices. The state processing network implements both the time based transition triggers and the event based transition triggers after being initiated by the IoT devices. Further, data structures, which record monitoring status of particular IoT devices, are compiled. Finally, the state processing network further selects an alternative action to trigger, and triggers the selected action using at least some data from a particular event being processed.