公开(公告)号：US20240070685A1

公开(公告)日：2024-02-29

申请号：US18243166

申请日：2023-09-07

申请人： Capital One Services, LLC

发明人： Jiashen Fang ,  Joakim Klas Gunnar Fagerstedt Cedin ,  Kirk Brunson ,  Ryan Griffin ,  Cavan Spillane Stone

IPC分类号： G06Q30/0201 ,  G06F16/22 ,  G06F16/2455 ,  G06F16/28 ,  G06F16/901 ,  G06Q10/10

CPC分类号： G06Q30/0201 ,  G06F16/2264 ,  G06F16/24566 ,  G06F16/283 ,  G06F16/9024 ,  G06Q10/10

摘要： Multidimensional data analysis applications, including OLAP applications, simultaneously aggregate across many sets of dimensions. However, computing multidimensional aggregates is a performance bottleneck for OLAP data analysis applications. In order to improve the speed of interactive analysis, OLAP databases often precompute aggregates at various levels of detail and on various combinations of data attributes. However, the cost and speed of precomputation influences how frequently the aggregates can be brought up-to-date. Systems and methods disclosed herein provide graph based multidimensional analysis processing without pre-aggregating or precomputing the data along dimensional hierarchies, and by providing the results to the end user on-demand. Since preaggregation or precomputation of data along dimensional hierarchies is not necessary, implementations allow the end user to perform data analysis as soon as the data is available.

公开(公告)号：US11803865B2

公开(公告)日：2023-10-31

申请号：US17096661

申请日：2020-11-12

申请人： Capital One Services, LLC

发明人： Jiashen Fang ,  Joakim Fagerstedt Cedin ,  Kirk Brunson ,  Ryan Griffin ,  Cavan Spillane Stone

IPC分类号： G06Q30/0201 ,  G06F16/901 ,  G06Q10/10 ,  G06F16/28 ,  G06F16/2455 ,  G06F16/22

CPC分类号： G06Q30/0201 ,  G06F16/2264 ,  G06F16/24566 ,  G06F16/283 ,  G06F16/9024 ,  G06Q10/10

摘要： Multidimensional data analysis applications, including OLAP applications, simultaneously aggregate across many sets of dimensions. However, computing multidimensional aggregates is a performance bottleneck for OLAP data analysis applications. In order to improve the speed of interactive analysis, OLAP databases often precompute aggregates at various levels of detail and on various combinations of data attributes. However, the cost and speed of precomputation influences how frequently the aggregates can be brought up-to-date. Systems and methods disclosed herein provide graph based multidimensional analysis processing without pre-aggregating or precomputing the data along dimensional hierarchies, and by providing the results to the end user on-demand. Since preaggregation or precomputation of data along dimensional hierarchies is not necessary, implementations allow the end user to perform data analysis as soon as the data is available.

公开(公告)号：US20220148016A1

公开(公告)日：2022-05-12

申请号：US17096661

申请日：2020-11-12

申请人： Capital One Services, LLC

发明人： Jiashen Fang ,  Joakim Fagerstedt Cedin ,  Kirk Brunson ,  Ryan Griffin ,  Cavan Spillane Stone

IPC分类号： G06Q30/02 ,  G06F16/901 ,  G06F16/22 ,  G06F16/28 ,  G06F16/2455 ,  G06Q10/10

摘要： Multidimensional data analysis applications, including OLAP applications, simultaneously aggregate across many sets of dimensions. However, computing multidimensional aggregates is a performance bottleneck for OLAP data analysis applications. In order to improve the speed of interactive analysis, OLAP databases often precompute aggregates at various levels of detail and on various combinations of data attributes. However, the cost and speed of precomputation influences how frequently the aggregates can be brought up-to-date. Systems and methods disclosed herein provide graph based multidimensional analysis processing without pre-aggregating or precomputing the data along dimensional hierarchies, and by providing the results to the end user on-demand. Since preaggregation or precomputation of data along dimensional hierarchies is not necessary, implementations allow the end user to perform data analysis as soon as the data is available.