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公开(公告)号：US11797576B2
公开(公告)日：2023-10-24
申请号：US17410181
申请日：2021-08-24
发明人： Manish Anand Bhide , Prateek Goyal , Seema Nagar , Sougata Mukherjea , Kuntal Dey , Pramod Vadayadiyil Raveendran
IPC分类号： G06F16/28 , G06F16/22 , G06F21/62 , G06F16/2455 , G06F16/248
CPC分类号： G06F16/284 , G06F16/221 , G06F16/2282 , G06F16/248 , G06F16/24554 , G06F21/6227
摘要： A system and method is provided to selectively process and store tables of a relational database by calculating an overall data sensitivity score for each table based on predefined attribute rules; performing column-wise splitting of at least one of the tables into a first table and a second table based on the overall data sensitivity score of each table, thereby generating a total number of relational database tables; storing a first subset of the total number of relational database tables in a private cloud storage database in a distributed storage environment based on the overall data sensitivity scores of each of the total number of relational database tables; and storing a second subset of the total number of relational database tables in a public cloud storage database of the distributed storage environment based on the overall data sensitivity scores of each of the total number of relational database tables.
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公开(公告)号：US20220291840A1
公开(公告)日：2022-09-15
申请号：US17195729
申请日：2021-03-09
发明人： Manish Anand Bhide , Prateek Goyal , Seema Nagar , Pramod Vadayadiyil Raveendran , Sougata Mukherjea , Kuntal Dey
IPC分类号： G06F3/06
摘要： Application-specific prioritization of streaming data replication. Data streamed from connected devices is selectively replicated to data storage clusters based on needs of the applications being served by the data. Data characterization supports prioritized replication processing. Statistical metrics compare streaming data with estimated values to characterize the data for prioritization.
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公开(公告)号：US20240020299A1
公开(公告)日：2024-01-18
申请号：US17865214
申请日：2022-07-14
CPC分类号： G06F16/2386 , G06F16/211 , G06F16/2282
摘要： An example operation may include one or more of storing a batch scoring engine and an application programming interface (API) for the batch scoring engine, receiving a trigger to perform a batch prediction process, reading input data from a source data store and executing, via the batch scoring engine, one or more predictive models on the input data to generate a predictive output and metadata associated with the predictive output, storing the predictive output and the metadata in a target data store, and updating the API with a location of the predictive output within the target data store and a location of the metadata within the target data store.
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公开(公告)号：US11693579B2
公开(公告)日：2023-07-04
申请号：US17195729
申请日：2021-03-09
发明人： Manish Anand Bhide , Prateek Goyal , Seema Nagar , Pramod Vadayadiyil Raveendran , Sougata Mukherjea , Kuntal Dey
IPC分类号： G06F3/06
CPC分类号： G06F3/065 , G06F3/0604 , G06F3/067 , G06F3/0614 , G06F3/0659
摘要： Application-specific prioritization of streaming data replication. Data streamed from connected devices is selectively replicated to data storage clusters based on needs of the applications being served by the data. Data characterization supports prioritized replication processing. Statistical metrics compare streaming data with estimated values to characterize the data for prioritization.
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公开(公告)号：US12008366B2
公开(公告)日：2024-06-11
申请号：US17805233
申请日：2022-06-03
IPC分类号： G06F8/77
CPC分类号： G06F8/77
摘要： Early indications of application programming interface (API) usage are identified by correlation to particular issues with the API including singular and mutual consistency, completeness, accuracy, and staleness. Analysis of API input and output along with data type and formatting information facilitates identification of the API issues. Establishing a correlation between API usage and issues supports early detection of potential usage reduction on a case-by-case level. Corrective action to resolve identified issues may be performed in a timely manner to maintain usage levels.
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公开(公告)号：US20230066677A1
公开(公告)日：2023-03-02
申请号：US17410181
申请日：2021-08-24
发明人： Manish Anand Bhide , Prateek Goyal , Seema Nagar , Sougata Mukherjea , Kuntal Dey , Pramod Vadayadiyil Raveendran
IPC分类号： G06F16/28 , G06F16/22 , G06F16/2455 , G06F16/248 , G06F21/62
摘要： A system and method is provided to selectively process and store tables of a relational database by calculating an overall data sensitivity score for each table based on predefined attribute rules; performing column-wise splitting of at least one of the tables into a first table and a second table based on the overall data sensitivity score of each table, thereby generating a total number of relational database tables; storing a first subset of the total number of relational database tables in a private cloud storage database in a distributed storage environment based on the overall data sensitivity scores of each of the total number of relational database tables; and storing a second subset of the total number of relational database tables in a public cloud storage database of the distributed storage environment based on the overall data sensitivity scores of each of the total number of relational database tables.
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公开(公告)号：US20220300453A1
公开(公告)日：2022-09-22
申请号：US17202559
申请日：2021-03-16
发明人： Manish Anand Bhide , Seema Nagar , Prateek Goyal , Kuntal Dey
摘要： One or more computer processors determine a storage strategy for each chunked data block in a training dataset based on a respective computed usefulness score and a series of usefulness thresholds, wherein the storage strategy comprises RAID strategies that include striping, mirroring, parity, and double parity. The one or more computer processors distribute each data block in the training dataset according to the respective determined storage strategy.
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公开(公告)号：US12061600B2
公开(公告)日：2024-08-13
申请号：US17865214
申请日：2022-07-14
CPC分类号： G06F16/2386 , G06F16/211 , G06F16/2282
摘要： An example operation may include one or more of storing a batch scoring engine and an application programming interface (API) for the batch scoring engine, receiving a trigger to perform a batch prediction process, reading input data from a source data store and executing, via the batch scoring engine, one or more predictive models on the input data to generate a predictive output and metadata associated with the predictive output, storing the predictive output and the metadata in a target data store, and updating the API with a location of the predictive output within the target data store and a location of the metadata within the target data store.
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公开(公告)号：US11809373B2
公开(公告)日：2023-11-07
申请号：US17202559
申请日：2021-03-16
发明人： Manish Anand Bhide , Seema Nagar , Prateek Goyal , Kuntal Dey
摘要： One or more computer processors determine a storage strategy for each chunked data block in a training dataset based on a respective computed usefulness score and a series of usefulness thresholds, wherein the storage strategy comprises RAID strategies that include striping, mirroring, parity, and double parity. The one or more computer processors distribute each data block in the training dataset according to the respective determined storage strategy.
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公开(公告)号：US20230214276A1
公开(公告)日：2023-07-06
申请号：US17646994
申请日：2022-01-04
IPC分类号： G06F9/54
CPC分类号： G06F9/541
摘要： A computer implemented method manages an artificial intelligence model. A number of processor units detect a change in a format used to exchange information between the artificial intelligence model and an application using the artificial intelligence model. The number of processor units changes the format of the information into an expected format used by the artificial intelligence model and the application. The number of processor units exchanges the information between the artificial intelligence model and the application using the expected format.
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