Abstract: Systems and methods for providing a universal format driven data transformation. In conventional ETL operations, the transform process that transforms data from the source format to the destination format is based on a transformation program. Conventionally, transform logic is developed around the chosen transform program. In accordance with an embodiment, a universal, format-driven data transform can be achieved through the use of a data transformation format. In accordance with an embodiment, a method for providing a universal format driven data transformation can include providing a transformation format in a file, wherein the transformation format is in a human-readable form; and providing, in the transformation format, keywords defining a target table type, a dataset list, and dataset operations to be performed on a dataset from the dataset list.

Abstract: Systems and methods for providing a universal format driven data transformation. In conventional ETL operations, the transform process that transforms data from the source format to the destination format is based on a transformation program. Conventionally, transform logic is developed around the chosen transform program. In accordance with an embodiment, a universal, format-driven data transform can be achieved through the use of a data transformation format. In accordance with an embodiment, a method for providing a universal format driven data transformation can include providing a transformation format in a file, wherein the transformation format is in a human-readable form; and providing, in the transformation format, keywords defining a target table type, a dataset list, and dataset operations to be performed on a dataset from the dataset list.

Abstract: In accordance with an embodiment, described herein are systems and methods for data pipeline optimization with an analytic applications environment. The system can determine historical performance data or statistics associated with data pipeline processes recorded over a period of time. The system can automatically determine an order of running jobs associated with the flow of data, while honoring functional dependencies, to reduce or otherwise optimize an overall time to load data to a data warehouse. For example, the system can use the historical data to estimate a time for current or upcoming tasks, or organize various tasks to run in sequence and/or in parallel, to arrive at a minimum time to run an activation plan for one or more tenants. The described approach enables fine-grained monitoring of statistics of ongoing jobs, prediction of potential issues, and communication of alerts where appropriate to address such issues ahead of time.

Abstract: Systems and methods for providing a universal format driven data transformation. In conventional ETL operations, the transform process that transforms data from the source format to the destination format is based on a transformation program. Conventionally, transform logic is developed around the chosen transform program. In accordance with an embodiment, a universal, format-driven data transform can be achieved through the use of a data transformation format. In accordance with an embodiment, a method for providing a universal format driven data transformation can include providing a transformation format in a file, wherein the transformation format is in a human-readable form; and providing, in the transformation format, keywords defining a target table type, a dataset list, and dataset operations to be performed on a dataset from the dataset list.

Abstract: A cloud-based ETL system provides error detection, error correction and reporting of data integration flows hosted by cloud services. Categories of errors are identified using one or more checks at different points of a data integration flow and one or more actions selected based at least in part on the error category. A determination can be made whether the error category is fault tolerant and one or more actions can be selected based at least in part on the error fault tolerance to correct the error, restart a flow, or generate a notification assisting a user to correct the error.

Abstract: A cloud-based ETL system provides error detection, error correction and reporting of data integration flows hosted by cloud services. Categories of errors are identified using one or more checks at different points of a data integration flow and one or more actions selected based at least in part on the error category. A determination can be made whether the error category is fault tolerant and one or more actions can be selected based at least in part on the error fault tolerance to correct the error, restart a flow, or generate a notification assisting a user to correct the error.

Abstract: There are significant advantages to employing a diverse workforce within an enterprise. Techniques for identifying gaps in diversity hiring, promotion, and termination within an enterprise are provided herein. The techniques described herein may be used to analyze any large data set for comparison of aggregated data. Employment data may be collected and aggregated based on classifications such as ethnicity, gender, veteran status, disability status, and so forth, and within each classification the data can be aggregated for hiring, termination, promotion, and so forth. Two aggregates can be identified for comparison, and statistical scores may be generated for the first aggregate as compared to the second aggregate. Each of the statistical scores may be weighted and the scores may be combined to generate a single impact score. The impact score can be used to identify gaps in diversity employment practices within the enterprise.

Abstract: A cloud-based ETL system provides error detection, error correction and reporting of data integration flows hosted by cloud services. Categories of errors are identified using one or more checks at different points of a data integration flow and one or more actions selected based at least in part on the error category. A determination can be made whether the error category is fault tolerant and one or more actions can be selected based at least in part on the error fault tolerance to correct the error, restart a flow, or generate a notification assisting a user to correct the error.

Abstract: A cloud-based ETL system provides error detection, error correction and reporting of data integration flows hosted by cloud services. Categories of errors are identified using one or more checks at different points of a data integration flow and one or more actions selected based at least in part on the error category. A determination can be made whether the error category is fault tolerant and one or more actions can be selected based at least in part on the error fault tolerance to correct the error, restart a flow, or generate a notification assisting a user to correct the error.