Abstract: A computer system is configured to receiving a data set from a data provider and automatically save the data set in a quarantine database where copying, moving, and sharing of the data set are restricted until the data set is released by a data provider. The data set is parsed to find and mark portions with potentially sensitive information. At least those parts are reviewed by a data governor, who can confirm, add, edit, or remove markers. Those parts can be visually indicated to the data governor, along with a preview of, metadata about, and analysis of the data set. After reviewing at least the automatically marked portions, the data governor can release the data set to a non-quarantine database where another user can use the data set. The user is restricted from accessing the quarantine database.

Abstract: An apparatus, and a method, performed by one or more processors are disclosed. The method receives a build request associated with performing an external data processing task on a first data set, the first data set being stored in memory associated with a data processing platform to be performed at a system external to the data processing platform. The method generates a task identifier for the data processing task, and provides, in association with the task identifier, the first data set to an agent associated with the external system with an indication of the data processing task, the agent being arranged to cause performance of the task at the external system, to receive a second data set resulting from performance of the task, and to provide the second data set and associated metadata indicative of the transformation. The method receives the second data set and metadata from the agent associated with the external system and stores the second data set and associated metadata.

Abstract: An apparatus, and a method, performed by one or more processors are disclosed. The method receives a build request associated with performing an external data processing task on a first data set, the first data set being stored in memory associated with a data processing platform to be performed at a system external to the data processing platform. The method generates a task identifier for the data processing task, and providing, in association with the task identifier, the first data set to an agent associated with the external system with an indication of the data processing task, the agent being arranged to cause performance of the task at the external system, to receive a second data set resulting from performance of the task, and to provide the second data set and associated metadata indicative of the transformation. The method receives the second data set and metadata from the agent associated with the external system and stores the second data set and associated metadata.

Abstract: The present disclosure relates to systems and techniques for developing APIs that utilize multiple pre-existing APIs. The present disclosure also relates to a user interface that allows for chaining APIs together as a function of multiple pre-existing APIs. The present disclosure also relates to security and authorization of a user to execute one or more APIs as part of an API chain.

Abstract: An apparatus, and a method, performed by one or more processors are disclosed. The method may comprise receiving a build request associated with performing an external data processing task on a first data set, the first data set being stored in memory associated with a data processing platform to be performed at a system external to the data processing platform. The method may also comprise generating a task identifier for the data processing task, and providing, in association with the task identifier, the first data set to an agent associated with the external system with an indication of the data processing task, the agent being arranged to cause performance of the task at the external system, to receive a second data set resulting from performance of the task, and to provide the second data set and associated metadata indicative of the transformation.

Abstract: The present disclosure relates to systems and techniques for developing APIs that utilize multiple pre-existing APIs. The present disclosure also relates to a user interface that allows for chaining APIs together as a function of multiple pre-existing APIs. The present disclosure also relates to security and authorization of a user to execute one or more APIs as part of an API chain.

Abstract: An apparatus, and a method, performed by one or more processors are disclosed. The method may comprise receiving a build request associated with performing an external data processing task on a first data set, the first data set being stored in memory associated with a data processing platform to be performed at a system external to the data processing platform. The method may also comprise generating a task identifier for the data processing task, and providing, in association with the task identifier, the first data set to an agent associated with the external system with an indication of the data processing task, the agent being arranged to cause performance of the task at the external system, to receive a second data set resulting from performance of the task, and to provide the second data set and associated metadata indicative of the transformation.

Abstract: A computer system is configured to receiving a data set from a data provider and automatically save the data set in a quarantine database where copying, moving, and sharing of the data set are restricted until the data set is released by a data provider. The data set is parsed to find and mark portions with potentially sensitive information. At least those parts are reviewed by a data governor, who can confirm, add, edit, or remove markers. Those parts can be visually indicated to the data governor, along with a preview of, metadata about, and analysis of the data set. After reviewing at least the automatically marked portions, the data governor can release the data set to a non-quarantine database where another user can use the data set. The user is restricted from accessing the quarantine database.

Abstract: A computer system is configured to receiving a data set from a data provider and automatically save the data set in a quarantine database where copying, moving, and sharing of the data set are restricted until the data set is released by a data provider. The data set is parsed to find and mark portions with potentially sensitive information. At least those parts are reviewed by a data governor, who can confirm, add, edit, or remove markers. Those parts can be visually indicated to the data governor, along with a preview of, metadata about, and analysis of the data set. After reviewing at least the automatically marked portions, the data governor can release the data set to a non-quarantine database where another user can use the data set. The user is restricted from accessing the quarantine database.

Abstract: An apparatus, and a method, performed by one or more processors are disclosed. The method may comprise receiving a build request associated with performing an external data processing task on a first data set, the first data set being stored in memory associated with a data processing platform to be performed at a system external to the data processing platform. The method may also comprise generating a task identifier for the data processing task, and providing, in association with the task identifier, the first data set to an agent associated with the external system with an indication of the data processing task, the agent being arranged to cause performance of the task at the external system, to receive a second data set resulting from performance of the task, and to provide the second data set and associated metadata indicative of the transformation.

Abstract: An apparatus, and a method, performed by one or more processors are disclosed. The method may comprise receiving a build request associated with performing an external data processing task on a first data set, the first data set being stored in memory associated with a data processing platform to be performed at a system external to the data processing platform. The method may also comprise generating a task identifier for the data processing task, and providing, in association with the task identifier, the first data set to an agent associated with the external system with an indication of the data processing task, the agent being arranged to cause performance of the task at the external system, to receive a second data set resulting from performance of the task, and to provide the second data set and associated metadata indicative of the transformation.

Abstract: An apparatus, and a method, performed by one or more processors are disclosed. The method may comprise receiving a build request associated with performing an external data processing task on a first data set, the first data set being stored in memory associated with a data processing platform to be performed at a system external to the data processing platform. The method may also comprise generating a task identifier for the data processing task, and providing, in association with the task identifier, the first data set to an agent associated with the external system with an indication of the data processing task, the agent being arranged to cause performance of the task at the external system, to receive a second data set resulting from performance of the task, and to provide the second data set and associated metadata indicative of the transformation.

Abstract: A computer system implements a risk model for detecting outliers in a large plurality of transaction data, which can encompass millions or billions of transactions in some instances. The computing system comprises a non-transitory computer readable storage medium storing program instructions for execution by a computer processor in order to cause the computing system to receive first features for an entity in the transaction data, receive second features for a benchmark set, the second features corresponding with the first features, determine an outlier value of the entity based on a Mahalanobis distance from the first features to a benchmark value representing an average for the second features. The output of the risk model can be used to prioritize review by a human data analyst. The data analyst's review of the underlying data can be used to improve the model.