Abstract: Synching multiple streams in a complex enterprise product by collecting and analyzing stream dependency data. Collection and analysis of data for large scale and complex enterprise results in a multi-dimensional relationship diagram that highlights the interconnected dependencies of the streams. This allows enterprise software users to more easily determine and select which stream (or streams) will help the user to perform a given task.

Abstract: A method, system and computer program product for container image migration service is provided. The method comprises identifying a latest version of a first customer container image stored in a container image repository. The method further comprises determining the latest version of the first customer container image is a migration image from a last version of the first customer container image; determining a set of commands in the Docker file of the last version of the first customer container image that have migrated to a corresponding set of commands in the Docker file of the migration image; identifying a latest version of a second customer container image having at least one Docker file command in common with at least one command in the set of commands; and recommending imminent migration of the second customer container image to include migration of the at least one Docker file command.

Abstract: A method, system and computer program product for container image migration service is provided. The method comprises identifying a latest version of a first customer container image stored in a container image repository. The method further comprises determining the latest version of the first customer container image is a migration image from a last version of the first customer container image; determining a set of commands in the Docker file of the last version of the first customer container image that have migrated to a corresponding set of commands in the Docker file of the migration image; identifying a latest version of a second customer container image having at least one Docker file command in common with at least one command in the set of commands; and recommending imminent migration of the second customer container image to include migration of the at least one Docker file command.

Abstract: An approach to optimize performance for large scale inference models. Data in the form of images is received from sensors such as cameras. The data is processed to generate data tags associated with the context of the image and portion the images. Model tags are generated based on data characteristics or user input. The tags and their associated data are added to a time-based queue for delivery to the appropriate inference models. Based on the embedded delivery time and frequency, the portioned images are delivered to the appropriate inference models.

Abstract: Synching multiple streams in a complex enterprise product by collecting and analyzing stream dependency data. Collection and analysis of data for large scale and complex enterprise results in a multi-dimensional relationship diagram that highlights the interconnected dependencies of the streams. This allows enterprise software users to more easily determine and select which stream (or streams) will help the user to perform a given task.

Abstract: A method includes predicting, using a machine learning model and based on a received set of user interactions on keywords appearing in a presentation, a knowledge background of the user indicating the user's degree of understanding of the presentation. The method also includes generating, based on the predicted knowledge background, a message comprising a description of a keyword in the presentation and coordinates where the description is to be positioned in the presentation and communicating the message to a device of the user.

Abstract: In an approach for maintaining data synchronization, a processor scans a set of data fields at each stage of a data analysis process. A processor generates a relationship tree model, wherein the set of data fields each correspond to a node in the relationship tree model. A processor prunes the relationship tree model. Responsive to an update to a data field of the set of data fields, a processor promulgates the update using the relationship tree model to generate an updated set of insight data. A processor outputs the updated set of insight data.

Abstract: A computer-implemented method includes receiving, at a datastore having a plurality of records of a transaction-monitoring system, a first record representing a first instance of a transaction. The datastore includes a first layer and a second layer. A first record hash code, based on the first record, is compared to a template hash code set that includes one or more template hash codes, where each template hash code corresponds to a respective transaction in a set of one or more known transactions. The first record is inserted into the first layer of the datastore. The first record is inserted into the second layer of the datastore, based at least in part on the first record hash code not being found in the template hash code set.

Abstract: In an approach for maintaining data synchronization, a processor scans a set of data fields at each stage of a data analysis process. A processor generates a relationship tree model, wherein the set of data fields each correspond to a node in the relationship tree model. A processor prunes the relationship tree model. Responsive to an update to a data field of the set of data fields, a processor promulgates the update using the relationship tree model to generate an updated set of insight data. A processor outputs the updated set of insight data.

Abstract: An on-demand key performance indicator (KPI) monitoring system includes an on-demand KPI structure module configured to dynamically generate an on-demand data structure of a KPI based on a KPI request input to a user interface. The KPI request includes a one or more targeted KPI objects. An agent collector module generates an on-demand KPI collection strategy based on the on-demand data structure. An object monitoring module collects KPI objects based on the on-demand KPI collection strategy. The collected KPI objects include the targeted KPI objects requested by the user, while excluding non-targeted KPI objects excluded from the user's KPI request.

Abstract: A computer-implemented method includes receiving, at a datastore having a plurality of records of a transaction-monitoring system, a first record representing a first instance of a transaction. The datastore includes a first layer and a second layer. A first record hash code, based on the first record, is compared to a template hash code set that includes one or more template hash codes, where each template hash code corresponds to a respective transaction in a set of one or more known transactions. The first record is inserted into the first layer of the datastore. The first record is inserted into the second layer of the datastore, based at least in part on the first record hash code not being found in the template hash code set.