Oracle International Corporation

Frank Patrick Abbott, Jr

Robert O Wyman

Cathleen Susan Wharton

John Mitchell Black, Iii

Jitesh Bakul Jhatakia

George E Noble

Scott Adrian Ellett

Carl William Luehr

Anthony Joseph Braun

Techniques for generating action recommendations for a data tape system are disclosed. A data tape system generates action recommendations for a data tape based on library-based metadata messages as well as a measured data quality value of the data tape. The system initiates an operation resulting in the data tape interacting with a media drive. A data tape library controller generates one or more metadata messages based on a result of a requested operation. The metadata message may include information regarding the type of error and a default recommended course of action. The system generates the recommended action for the data tape using a trained machine learning model.

Data tape media quality validation and action recommendation

Techniques for determining a data tape read quality value are disclosed. A data tape system generates a value representing a quality of a data tape based on attributes of the data tape. The system calculates the data quality value using an algorithm based on: (a) a particular data tape error correction value, (b) data tape length value representing a length of data tape traversed during data-processing operations, and (c) a scaling factor. The scaling factor is based on a relationship between the particular data tape error correction value and a rate of degradation of the data tape. The scaling factor may be generated by applying a trained machine learning model to attributes of a data tape. The model generates a scaling factor for a particular data tape based on the attributes of the particular data tape.

Data tape quality analysis

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Brighton, CO, United States of America

Frank Patrick Abbott, Jr