Abstract: Job execution can be scheduled and monitored. Execution of a job results in generation of one or more data slices, which can be consumed as input by one or more related jobs. Data slices can be presented in an interactive view. Selection of a data slice in the view can trigger automatic identification of related data slices based on dependencies between data slices. Each data slice can also include and be presented with a status indicating the availability of corresponding data, such as pending, ready, or failed. Furthermore, selection of a data slice that failed to generate successfully can trigger identification of related data slices that failed or are predicted to fail to generate successfully.

Abstract: The subject disclosure relates to techniques for providing data experience(s) via disparate semantic annotations based on a respective user scenario. Semantic information for respective data types of data set(s) may be received. The data types may be annotated based on the semantic information to obtain respective data annotations. In response to receipt of a search query from a client, a search result that includes at least a portion of one or more data annotations is generated to be sent to the client. The search query may request performance of a search against the semantic information to obtain first semantic information associated with first data type(s) of the data types. The portion of the one or more data annotations may include the first semantic information. The first semantic information may describe operation(s) to be performed on data of at least one of the first data type(s).

Abstract: Job execution can be scheduled and monitored. Execution of a job results in generation of one or more data slices, which can be consumed as input by one or more related jobs. Data slices can be presented in an interactive view. Selection of a data slice in the view can trigger automatic identification of related data slices based on dependencies between data slices. Each data slice can also include and be presented with a status indicating the availability of corresponding data, such as pending, ready, or failed. Furthermore, selection of a data slice that failed to generate successfully can trigger identification of related data slices that failed or are predicted to fail to generate successfully.

Abstract: The subject disclosure relates to techniques for providing data experience(s) via disparate semantic annotations based on a respective user scenario. An annotation component can synthesize semantic information for respective data types of data set(s), associate the semantic information with the respective data types to obtain respective data annotations, and in response to receiving a query from a client, send at least a portion of the respective data annotations to the client. Further, a data aggregation component can aggregate the respective data annotations and at least a portion of the data set(s). Other embodiments relate to performing, via an application, operations utilizing a data type based on respective semantic annotations associated with the data type. Yet other embodiments relate to receiving external data annotation(s) and associating the external data annotation(s) with portion(s) of the respective data types to derive portion(s) of the respective semantic annotations.

Abstract: A view of data transformation jobs can be presented by way of a user interface. Related jobs can subsequently be identified automatically after a job is selected based on data dependencies between jobs. Execution status can also be determined and presented such that successful and failed execution of jobs, for example, can be differentiated. Furthermore, selection of a job run that failed to execute successfully can trigger identification of related jobs runs that failed or are predicted to fail to execute successfully.

Abstract: A view of data transformation jobs can be presented by way of a user interface. Related jobs can subsequently be identified automatically after a job is selected based on data dependencies between jobs. Execution status can also be determined and presented such that successful and failed execution of jobs, for example, can be differentiated. Furthermore, selection of a job run that failed to execute successfully can trigger identification of related jobs runs that failed or are predicted to fail to execute successfully.

Abstract: Jobs can be authored in conjunction with a visual workspace. Upon selection of representation of a data source in the workspace, a preview of the data source can be generated within context of the visual workspace. Further, representations of one or more data transformation operations can be provided with the preview. Selection of a transformation operation results in an updated preview reflecting application of the operation as well as generation of backend code to perform the operation. Furthermore, a job comprising one or more transformation operations can be added to the workspace automatically.

Abstract: Jobs can be created within a visual authoring environment. A new job of a selected type can be added to a diagrammatic workspace. Subsequently, a mechanism configured to enable selection of a saved job that implements all or a portion of the job can be presented. After selection, a saved job can be acquired and the workspace updated based thereon. Furthermore, data sources associated with the saved job can be can be added to a data source designated portion of the environment.