Abstract: An approach for transforming a large dataset using user interface-based transformations applied to a sample of the dataset is disclosed. The sample of the large dataset has the same or similar format as the large dataset. A user can quickly apply transformations to the sample dataset using UI-based instructions. The UI-based instructions can be used to create a transformation job that can be configured to run on a backed database, such as a distributed database, to apply the transformations to the large dataset.

Abstract: An approach for transforming a large dataset using user interface-based transformations applied to a sample of the dataset is disclosed. The sample of the large dataset has the same or similar format as the large dataset. A user can quickly apply transformations to the sample dataset using UI-based instructions. The UI-based instructions can be used to create a transformation job that can be configured to run on a backed database, such as a distributed database, to apply the transformations to the large dataset.

Abstract: The present technology provides a workflow engine that creates custom workflows of sequential tasks with various dependencies and an input of a particular dataset of objects that needs to be operated on or analyzed to result in an intended output. The customization can include a number and order of sequential workflow steps as well as a number and function of jobs to be executed in parallel at each of the workflow steps. When the workflow jobs are ready to be run, they may be queued up with an asynchronous task message server that services a server that supports near real-time communications. The asynchronous task service may be a message-oriented middleware that provides a queue to parallelize tasks.

Abstract: An approach for transforming a large dataset using user interface-based transformations applied to a sample of the dataset is disclosed. The sample of the large dataset has the same or similar format as the large dataset. A user can quickly apply transformations to the sample dataset using UI-based instructions. The UI-based instructions can be used to create a transformation job that can be configured to run on a backed database, such as a distributed database, to apply the transformations to the large dataset.

Abstract: An approach for transforming a large dataset using user interface-based transformations applied to a sample of the dataset is disclosed. The sample of the large dataset has the same or similar format as the large dataset. A user can quickly apply transformations to the sample dataset using UI-based instructions. The UI-based instructions can be used to create a transformation job that can be configured to run on a backed database, such as a distributed database, to apply the transformations to the large dataset.

Abstract: An approach for transforming a large dataset using user interface-based transformations applied to a sample of the dataset is disclosed. The sample of the large dataset has the same or similar format as the large dataset. A user can quickly apply transformations to the sample dataset using UI-based instructions. The UI-based instructions can be used to create a transformation job that can be configured to run on a backed database, such as a distributed database, to apply the transformations to the large dataset.

Abstract: An approach for transforming a large dataset using user interface-based transformations applied to a sample of the dataset is disclosed. The sample of the large dataset has the same or similar format as the large dataset. A user can quickly apply transformations to the sample dataset using UI-based instructions. The UI-based instructions can be used to create a transformation job that can be configured to run on a backed database, such as a distributed database, to apply the transformations to the large dataset.

Abstract: An approach for transforming a large dataset using user interface-based transformations applied to a sample of the dataset is disclosed. The sample of the large dataset has the same or similar format as the large dataset. A user can quickly apply transformations to the sample dataset using UI-based instructions. The UI-based instructions can be used to create a transformation job that can be configured to run on a backed database, such as a distributed database, to apply the transformations to the large dataset.

Abstract: An approach for transforming a large dataset using user interface-based transformations applied to a sample of the dataset is disclosed. The sample of the large dataset has the same or similar format as the large dataset. A user can quickly apply transformations to the sample dataset using UI-based instructions. The UI-based instructions can be used to create a transformation job that can be configured to run on a backed database, such as a distributed database, to apply the transformations to the large dataset.