Abstract: Generating Notifications Through Chart Pattern Detection Embodiments utilize pattern recognition to generate notifications in connection with analytical applications. A dashboard of the analytical dashboard is scanned to intake charts of data therefrom. Images of the charts are created, and then matched with repository patterns of a trained deep transfer model (such as a Convolutional Neural Network model). Upon matching of a pattern by the model, an alert is generated and communicated to a user to indicate a trend in the analytical data. In this manner, embodiments automatically detect data trends based upon their visual appearance when plotted in a chart, rather than through resource-intensive analysis of individual data point values. In specific embodiments, the pattern recognition may be implemented by an in-memory database engine of an in-memory database responsible for storing charts and/or chart images and/or the repository.

Abstract: Embodiments store attributes extracted from incoming media data (e.g., image, audio, video), in a media store residing in a data lake together with other, non-media attributes. In response to incoming media data (e.g., an image), an engine references an unpopulated media attribute schema resulting from processing a trained deep learning model (e.g., a Convolutional Neural Network—CNN model). The engine applies the deep learning model to extract from the incoming media data, a media attribute (e.g., a cloudy spot dimension) comprising a prediction value and a confidence. The engine populates the media attribute schema with the attribute (value; confidence) and an identifier, and stores the populated media attribute schema in the data lake. The data lake also includes a non-media attribute (e.g., patient info) sharing the identifier. Now, the data lake may be queried for both the non-media (patient info) attribute and the media (image) attribute extracted by the model.

Abstract: Embodiments store attributes extracted from incoming media data (e.g., image, audio, video), in a media store residing in a data lake together with other, non-media attributes. In response to incoming media data (e.g., an image), an engine references an unpopulated media attribute schema resulting from processing a trained deep learning model (e.g., a Convolutional Neural Network—CNN model). The engine applies the deep learning model to extract from the incoming media data, a media attribute (e.g., a cloudy spot dimension) comprising a prediction value and a confidence. The engine populates the media attribute schema with the attribute (value; confidence) and an identifier, and stores the populated media attribute schema in the data lake. The data lake also includes a non-media attribute (e.g., patient info) sharing the identifier. Now, the data lake may be queried for both the non-media (patient info) attribute and the media (image) attribute extracted by the model.

Abstract: Partitions are enabled to be merged in storage device of distributed database systems. A request to merge a plurality of source partitions into a merged partition is received. Each source partition stores a plurality of data items having corresponding source global identifiers and corresponding source local identifiers. The data items, with corresponding metadata, are appended from the source partitions to an intermediate storage structure in an order defined by the source local identifiers. Target global identifiers and target local identifiers are generated for each of the data items in the intermediate storage structure. The copied data items are flushed from the intermediate storage structure to the merged partition in an order defined by the target global identifiers. The source partitions and intermediate storage structure may then be purged of data, removed, and/or reused for further storage needs.

Abstract: A process for providing a plurality of exploration mode charts to supplement a base chart is provided herein. A request for exploration mode charts may be received. The request may include a data set definition. A total number of data points for the request may be determined based on the data set definition. A total number of exploration mode charts may be determined based at least in part on the total number of data points for the request. Chart data may be obtained for a plurality of exploration mode charts based on the data set definition. The plurality of exploration mode charts may include a number of charts less than or equal to the total number of exploration mode charts. The plurality of exploration mode charts may be rendered via the chart data. The rendered exploration mode charts may be provided.

Abstract: Partitions are enabled to be merged in storage device of distributed database systems. A request to merge a plurality of source partitions into a merged partition is received. Each source partition stores a plurality of data items having corresponding source global identifiers and corresponding source local identifiers. The data items, with corresponding metadata, are appended from the source partitions to an intermediate storage structure in an order defined by the source local identifiers. Target global identifiers and target local identifiers are generated for each of the data items in the intermediate storage structure. The copied data items are flushed from the intermediate storage structure to the merged partition in an order defined by the target global identifiers. The source partitions and intermediate storage structure may then be purged of data, removed, and/or reused for further storage needs.

Abstract: A process for providing a plurality of exploration mode charts to supplement a base chart is provided herein. A request for exploration mode charts may be received. The request may include a data set definition. A total number of data points for the request may be determined based on the data set definition. A total number of exploration mode charts may be determined based at least in part on the total number of data points for the request. Chart data may be obtained for a plurality of exploration mode charts based on the data set definition. The plurality of exploration mode charts may include a number of charts less than or equal to the total number of exploration mode charts. The plurality of exploration mode charts may be rendered via the chart data. The rendered exploration mode charts may be provided.

Abstract: An application sender can control the distribution and use of an application using an authorization token encapsulating distribution terms submitted by the application sender and the application license specification submitted by a developer of the application. The application sender can access an application store and perform various functions such as selecting one or more applications for use by an application receiver, combining one or more applications into a bundle for use by an application receiver, and/or combining several applications to form a new application for use by an application receiver. The application receiver can utilize the application in accordance with the authorization token generated by the distribution terms.

Abstract: An application sender can control the distribution and use of an application using an authorization token encapsulating distribution terms submitted by the application sender and the application license specification submitted by a developer of the application. The application sender can access an application store and perform various functions such as selecting one or more applications for use by an application receiver, combining one or more applications into a bundle for use by an application receiver, and/or combining several applications to form a new application for use by an application receiver. The application receiver can utilize the application in accordance with the authorization token generated by the distribution terms.

Abstract: An application sender can control the distribution and use of an application using an authorization token encapsulating distribution terms submitted by the application sender and the application license specification submitted by a developer of the application. The application sender can access an application store and perform various functions such as selecting one or more applications for use by an application receiver, combining one or more applications into a bundle for use by an application receiver, and/or combining several applications to form a new application for use by an application receiver. The application receiver can utilize the application in accordance with the authorization token generated by the distribution terms.