Abstract: In the present disclosure, systems and methods are described for allowing a non-code user to create to transform a database in an ETL pipeline. Specifically, as disclosed herein, a user can take a database and receive a ruleset to apply to the database in an ETL pipeline. The data linting system may take the database and extract a schema and a data sample from it. Further, the data linting system may use the schema and data sample to create two rulesets. With these rulesets, the data linting system combines them to create a final ruleset which may be validated using the data sample. The data linting system then sends the final ruleset and the validation report to the user. With this system, the user only needs to give it a database and will receive a ruleset that is able to be immediately used in an ETL pipeline.

Abstract: In the present disclosure, systems and methods are described for allowing a non-code user to create to transform a database in an ETL pipleline. Specifically, as disclosed herein, a user can take a database and receive a ruleset to apply to the database in an ETL pipeline. The data linting system may take the database and extract a schema and a data sample from it. Further, the data linting system may use the schema and data sample to create two rulesets. With these rulesets, the data linting system combines them to create a final ruleset which may be validated using the data sample. The data linting system then sends the final ruleset and the validation report to the user. With this system, the user only needs to give it a database and will receive a ruleset that is able to be immediately used in an ETL pipeline.

Abstract: A data analysis server maintains database operation history data and context data for database operations performed on tables by a set of training users. The data analysis server builds predictive models for using the maintained data to recommend database operations and operands to a set of guided users. The data analysis server trains the predictive models by determining and weighting features derived from context data that are predictive of performing database operations to tables with similar context data. Using the predictive model, the data analysis server generates recommended database operations and operands based on context data received from a data analysis application of a guided user and sends the recommendations to the data analysis application for presentation to the guided user.

Abstract: A data analysis server maintains database operation history data and context data for database operations performed on tables by a set of training users. The data analysis server builds predictive models for using the maintained data to recommend database operations and operands to a set of guided users. The data analysis server trains the predictive models by determining and weighting features derived from context data that are predictive of performing database operations to tables with similar context data. Using the predictive model, the data analysis server generates recommended database operations and operands based on context data received from a data analysis application of a guided user and sends the recommendations to the data analysis application for presentation to the guided user.

Abstract: Apparatus, systems, and methods may operate to receive a first identification of two or more records that match and to search at least two sources of data to locate a set of potential matching records, based on element transformation to determine common characteristics of the two or more records. Further activities may include publishing the set of potential matching records, receiving a second identification of matching members of the set, and searching at least one repository to locate further matching records based on the second identification and the common characteristics. Additional apparatus, systems, and methods are disclosed.

Abstract: Apparatus, systems, and methods may operate to receive a first identification of two or more records that match and to search at least two sources of data to locate a set of potential matching records, based on element transformation to determine common characteristics of the two or more records. Further activities may include publishing the set of potential matching records, receiving a second identification of matching members of the set, and searching at least one repository to locate further matching records based on the second identification and the common characteristics. Additional apparatus, systems, and methods are disclosed.