Abstract: Aspects of the disclosure relate to apparatuses, method steps, and systems for optimized Internet of Things (IoT) data processing for real-time decision support systems. The systems are used for real-time processing prioritization using a prioritization code and/or processing code. Edge devices may generate processing codes that are used in optimizing the data processing. For example, the system receives sensor data and preprocesses the sensor data with a simplified state estimation module to calculate a variance that is used to determine a processing code and/or a prioritization code.

Abstract: Aspects of the disclosure relate to apparatuses, method steps, and systems for optimized Internet of Things (IoT) data processing for real-time decision support systems. The systems are used for real-time processing prioritization using a prioritization code and/or processing code. Edge devices may generate processing codes that are used in optimizing the data processing. For example, the system receives sensor data and preprocesses the sensor data with a simplified state estimation module to calculate a variance that is used to determine a processing code and/or a prioritization code.

Abstract: Aspects of the disclosure relate to apparatuses, method steps, and systems for optimized Internet of Things (IoT) data processing for real-time decision support systems. The systems are used for real-time processing prioritization using a prioritization code and/or processing code. Edge devices may generate processing codes that are used in optimizing the data processing. For example, the system receives sensor data and preprocesses the sensor data with a simplified state estimation module to calculate a variance that is used to determine a processing code and/or a prioritization code.

Abstract: Embodiments of the invention are directed to a system, method, or computer program product for analyzing a data model and identifying anomalies within the data model. Data stored in a database is transformed into a data model by the invention, wherein the invention analyzes the data and generates relationships between tables and information contained within to generate the model. The data model itself is then analyzed in order to accurately identify anomalies such as ragged hierarchies, many-to-many issues, and/or double counting issues present in the data model which might affect the data integrity. Upon analyzing the data model, the invention compiles lists of discovered information and presents the results to a user in the form of a data analysis report.

Abstract: Embodiments of the invention are directed to a system, method, or computer program product for analyzing a data model and identifying anomalies within the data model. Data stored in a database is transformed into a data model by the invention, wherein the invention analyzes the data and generates relationships between tables and information contained within to generate the model. The data model itself is then analyzed in order to accurately identify anomalies such as ragged hierarchies, many-to-many issues, and/or double counting issues present in the data model which might affect the data integrity. Upon analyzing the data model, the invention compiles lists of discovered information and presents the results to a user in the form of a data analysis report.