Abstract: Various embodiments comprise systems and methods to maintain data consistency in a data pipeline. In some examples, a computing system comprises data monitoring circuitry that monitors the operations of the data pipeline. The data pipeline receives input data, processes the input data, and generates output data. The data monitoring circuitry receives and processes the output data sets to identify changes between the output data sets. The data monitoring circuitry generates a consistency score based on the changes that indicates a similarity level between the output data sets. The data monitoring circuitry determines when the consistency score exceeds a threshold value. When the consistency score exceeds the threshold value, the data monitoring circuitry generates and transfers an alert that indicates ones of the output data sets that exceeded the threshold value.

Abstract: Various embodiments comprise systems and methods to sample data outputs of a data pipeline. In some examples, data monitoring circuitry monitors the data pipeline wherein the data pipeline receives an input data set, processes the input data set, and responsively generates and transfers an output data set. The data monitoring circuitry ingests the output data set, determines an amount of available computing resources, and selects an amount of the values from the output data set based on the amount of available computing resources. The data monitoring circuitry generates a quality score for the selected values based on a data quality, generates a confidence score based on the amount of the selected values, and reports the quality score and the confidence score.

Abstract: Various embodiments comprise systems and methods to monitor operations of a data pipeline. In some examples, a data pipeline receives data inputs, processes the data inputs, and responsively generates and transfers data outputs. Data monitoring circuitry monitors the operations of the data pipeline circuitry, identifies an input change between an initial one of the data inputs and a subsequent one of the data inputs, and identifies an output change between an initial one of the data outputs and a subsequent one of the data outputs. The data monitoring circuitry correlates the input change to the output change, determines a quality threshold for the output change based on the correlation, and determines when the output change falls below the quality threshold. When the output change falls below the quality threshold, the data monitoring circuitry generates and transfers an alert that indicates the input change and the output change.

Abstract: Various embodiments comprise systems and methods to maintain data consistency in a data pipeline. In some examples, a computing system comprises data monitoring circuitry that monitors the operations of the data pipeline. The data pipeline receives input data, processes the input data, and generates output data. The data monitoring circuitry receives and processes the output data sets to identify changes between the output data sets. The data monitoring circuitry generates a consistency score based on the changes that indicates a similarity level between the output data sets. The data monitoring circuitry determines when the consistency score exceeds a threshold value. When the consistency score exceeds the threshold value, the data monitoring circuitry generates and transfers an alert that indicates ones of the output data sets that exceeded the threshold value.

Abstract: Various embodiments comprise systems and methods to indicate when errors occur in a data pipeline. In some examples, data monitoring circuitry monitors the operations of a data pipeline. The data monitoring circuitry ingests an output data set generated by the pipeline, compares the output data set to an expected output, identifies differences between the output data set and the expected output, and determines when the magnitude of the difference exceeds an error threshold. When the error threshold is exceeded, the data monitoring circuitry generates a graphical representation of the output data set, a graphical representation of the expected pipeline output, and an animated transition from the graphical representation of the expected pipeline output to the graphical representation of the output data.

Abstract: Various embodiments include a data monitoring system that monitors the operations of a data pipeline. The data monitoring system receives a call from the data pipeline to ingest unprocessed data. The data monitoring system generates metadata based on the unprocessed data and responsively computes expected data outputs. The data monitoring system receives a call from the data pipeline to ingest processed data that comprises actual data outputs generated by the data pipeline. The data monitoring system generates output metadata based on the processed data. The data monitoring system compares the metadata for the expected data outputs with the output metadata for the actual data outputs and determines when the expected data outputs do not align with the actual data outputs. When the expected data outputs do not align with the actual data outputs, the data monitoring system generates and transfers an alert signifying the non-alignment.

Abstract: Systems and methods for data quality monitoring are provided. Various embodiments include a data monitoring system that integrates into a data pipeline. The data monitoring system may receive a call from the data pipeline to analyze data inputs entering the data pipeline. The monitoring system can generate metadata describing the data inputs and compare the generated metadata with previously generated metadata to determine if the data inputs are historically consistent. The data monitoring system may return a consistency measure to the data pipeline. In further embodiments, the data monitoring system can generate metadata describing data outputs from the data pipeline and compare the output metadata to previously generated output metadata. In further embodiments, the data monitoring system may operate as a read only entity in a database. The monitoring system may monitor for changes in the database and determine when adverse changes occur in the database.