Abstract: A digital assistant platform may receive a query relating to a target data file. The target data file may be associated with a standardized data set. The standardized data set may include data files that are aggregated based on data elements associated with the data files, and may be configured to enable a plurality of services. The digital assistant platform may extract, based on the query, one or more keywords, and identify an intent classification and an entity associated with the query. The digital assistant platform may analyze the plurality of services to identify a target service to enable, and analyze the data elements to identify the target data file. The digital assistant platform may determine, using the target service, analytical information associated with a data element of the target data file, and generate a response to the query based on the analytical information.

Abstract: A test automation platform may receive a test case for testing a data ingestion pipeline. The test automation platform may determine a test intent of the test case using a test intent identification model. The test automation platform may determine a type of entity associated with the data ingestion pipeline that the test case is to test using a test entity identification model. The test automation platform may generate a prediction of a data ingestion scenario for which the test case is to be applied based at least in part on the test intent of the test and the type of entity. The test automation platform may generate a mapping file representing the prediction of the data ingestion scenario. The test automation platform may execute, using test cases of the mapping file, a set of tests on a new data ingestion pipeline.

Abstract: A test automation platform may receive a test case for testing a data ingestion pipeline. The test automation platform may determine a test intent of the test case using a test intent identification model. The test automation platform may determine a type of entity associated with the data ingestion pipeline that the test case is to test using a test entity identification model. The test automation platform may generate a prediction of a data ingestion scenario for which the test case is to be applied based at least in part on the test intent of the test and the type of entity. The test automation platform may generate a mapping file representing the prediction of the data ingestion scenario. The test automation platform may execute, using test cases of the mapping file, a set of tests on a new data ingestion pipeline.

Abstract: A data platform may receive data files from an electronic data interchange (EDI). The data files may be received in multiple different data formats. The data platform may convert the data files to a common data format, extract data elements from the data files converted to the common data format, and assign the data elements extracted from the data files to file identifiers. The data platform may assign the data elements extracted from the data files to attribute identifiers that identify types of data represented by the data elements, aggregate the data elements to create a standardized data set, and map the data elements in the standardized data set to functions. The data platform may generate values based on mapping the data elements to the functions, determine a metric based on combining the values according to a metric definition, and post the metric to the EDI for consumption.

Abstract: A digital assistant platform may receive a query relating to a target data file. The target data file may be associated with a standardized data set. The standardized data set may include data files that are aggregated based on data elements associated with the data files, and may be configured to enable a plurality of services. The digital assistant platform may extract, based on the query, one or more keywords, and identify an intent classification and an entity associated with the query. The digital assistant platform may analyze the plurality of services to identify a target service to enable, and analyze the data elements to identify the target data file. The digital assistant platform may determine, using the target service, analytical information associated with a data element of the target data file, and generate a response to the query based on the analytical information.

Abstract: A data platform may receive data files from an electronic data interchange (EDI). The data files may be received in multiple different data formats. The data platform may convert the data files to a common data format, extract data elements from the data files converted to the common data format, and assign the data elements extracted from the data files to file identifiers. The data platform may assign the data elements extracted from the data files to attribute identifiers that identify types of data represented by the data elements, aggregate the data elements to create a standardized data set, and map the data elements in the standardized data set to functions. The data platform may generate values based on mapping the data elements to the functions, determine a metric based on combining the values according to a metric definition, and post the metric to the EDI for consumption.