Abstract: A computer-based system may be configured to collect metadata for each source and target defined for a data pipeline and formatting information (e.g., schemas, transformations, etc.) associated with each entity and field. During the definition of the pipeline, how the data will end up in the target may be defined, for example, by a user of the computer-based system via a GUI/interface and/or the like. Information (e.g., modification information, etc.) describing how the data will end up in the target may be defined, stored, and accessed to determine and/or track over which fields and entities are affected by the user-defined mutations and over which schemas. Lineage information (e.g., a genealogical tree, data lineage tracing, etc.) describing a data, version, and transformation may be generated and used to determine a source for a data record, how changes to the data record are related, how lineage evolved, and/or the like.

Abstract: Disclosed herein are system, method, and computer program product embodiments for implementing automatic taxonomy tags in an API microgateway. The API microgateway may receive a plurality of API requests for an API managed by a customer in a period of time and route the plurality of API request to an instance of the API according to a policy of the API. The API microgateway may aggregate metrics information related to the plurality of API requests. The aggregated metrics information may include request features, response features, policy features, and performance features. In response to a cluster of the metrics information corresponding to a tag in a tag prediction system, the aggregated metrics information may be labeled with the tag. The tag and the aggregated metrics information may be added to an access log and sent to the customer.

Abstract: A computer-based system may be configured to collect metadata and/or the like indicative of all the metrics exposed from a data pipeline (e.g., an ETL pipeline, etc.) and transform the metrics into a single group of metrics user-facing, user-specific, user-configured, and/or the like metrics that allow the maturity and quality of data and/or data records to be analyzed and/or displayed. Collected metrics can be agnostic of a source data flow component of a data pipeline and/or resource technology (e.g., API, etc.). Collected metrics may indicate a measure of data freshness, data duplication, new data records, updated date data records, data errors, and/or the like.

Abstract: Disclosed herein are system, method, and device embodiments for a data bridge adapter in a data integration platform that models any application programming interface as an entity-relationship model. This technique allows an individual using an integration platform to map and transform the entity-relationship model without having to create any custom code. The user may specify target parameters as part of an ETL process, and the entity relationship model may allow appropriate data and API calls to be generated to pass the data to the specified target. By creating an entity-relationship model from any API, the technique further supports versioning, schema change resolution, compatibility detection and other features. Furthermore, data visualization software may use the entity-relationship model to allow users to explore and analyze the data represented in the entity-relationship model.