Abstract: The present technology pertains to systems and methods for executing data transformations within cloud-based service environments, such as SaaS platforms. The technology disclosed herein utilizes logic blocks to perform data transformations, incorporating all necessary logic and metadata to propagate changes in data structure. In an embodiment, a method includes receiving input that specifies a desired data transformation, creating a logic block to define the transformation, developing a transformation plan, and executing the logic block as per the plan to alter data stored in identified tables. Generating the transformation plan includes identifying the tables that contain the data to be transformed. The system described herein allows for efficient, consistent, and secure data transformations across multiple tenants in a distributed cloud service environment.

Abstract: Technology disclosed herein includes systems and methods for transforming large amounts of transactional or system data with no downtime and little to no impact on the end user experience. More specifically, systems and methods for performing crawling data transforms are disclosed in which data transforms run as timed and throttled background processes to reduce the required processing resources and eliminate the need for downtime. A method for performing crawling data transforms includes generating transformation plans having multiple steps based on a transform definition, determining that a number of running plans is below a threshold, determining that a number of running steps is below a threshold, identifying an uncompleted table within a step of a transformation plan, and transforming records in the uncompleted table until all records in the table are transformed or the step is terminated.

Abstract: Various embodiments comprise systems and methods for providing customer-defined attributes (CDAs) in an enterprise resource planning platform. In an example, a method includes receiving a CDA definition defining a new data field for storing a new CDA and associating the new data field with a source data table as well as a data flow from the source data table to a destination data table. The method further includes initiating a business process including the data flow by generating a new record that includes the source data table and calling at least one logic block by passing information corresponding to the new CDA to the logic block. The logic block identifies the information corresponding to the new CDA and executes at least a portion of the data flow by passing the information corresponding to the new CDA from the source data table to a destination data table.

Abstract: The present technology pertains to systems and methods for executing data transformations within cloud-based service environments, such as SaaS platforms. The technology disclosed herein utilizes logic blocks to perform data transformations, incorporating all necessary logic and metadata to propagate changes in data structure. In an embodiment, a method includes receiving input that specifies a desired data transformation, creating a logic block to define the transformation, developing a transformation plan, and executing the logic block as per the plan to alter data stored in identified tables. Generating the transformation plan includes identifying the tables that contain the data to be transformed. The system described herein allows for efficient, consistent, and secure data transformations across multiple tenants in a distributed cloud service environment.