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公开(公告)号：US11379500B2
公开(公告)日：2022-07-05
申请号：US16879262
申请日：2020-05-20
Applicant: SAP SE
Inventor： Apoorv Bhargava , Daniel Zimmermann , Markus Goeppert , Syed Aleemuddin Noor , Gowthami Agumamidi
Abstract: Technologies are described for performing automated data integration, reconciliation, and/or self-healing using machine learning. For example, data integration can be checked using a reconciliation procedure. The number of times that the reconciliation is performed can be determined dynamically by a machine learning model. For each iteration, reconciliation can be performed to check integrated data against source data. If any reconciliation errors are found, then self-healing operations can be performed. Results of the reconciliation can be output. The reconciliation results can be used to update the machine learning model so that the machine learning model can dynamically adjust the number of iterations to perform based at least in part on reconciliation results.
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公开(公告)号：US20210303547A1
公开(公告)日：2021-09-30
申请号：US16879262
申请日：2020-05-20
Applicant: SAP SE
Inventor： Apoorv Bhargava , Daniel Zimmermann , Markus Goeppert , Syed Aleemuddin Noor , Gowthami Agumamidi
Abstract: Technologies are described for performing automated data integration, reconciliation, and/or self-healing using machine learning. For example, data integration can be checked using a reconciliation procedure. The number of times that the reconciliation is performed can be determined dynamically by a machine learning model. For each iteration, reconciliation can be performed to check integrated data against source data. If any reconciliation errors are found, then self-healing operations can be performed. Results of the reconciliation can be output. The reconciliation results can be used to update the machine learning model so that the machine learning model can dynamically adjust the number of iterations to perform based at least in part on reconciliation results.
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