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1. 发明公开

EP2312463A1 Data provider with transcient universe 审中-公开
标题翻译： Datenanbieter mit transienter Gesamtheit
公开(公告)号：EP2312463A1
公开(公告)日：2011-04-20
申请号：EP09290795.5
申请日：2009-10-16
申请人： Business Objects Software Ltd.
发明人： Le Biannic, Yann , O'Byrne, John , Calvente, Juan Francisco
IPC分类号： G06F17/30
CPC分类号： G06F17/30592
摘要： A computer-implemented system to receive an instruction to initialize a data provider associated with an analysis cube and a dataset, and, in response to the instruction, acquire first metadata associated with the analysis cube and generate, based on the first metadata, second metadata of an abstraction layer comprising a plurality of objects. A query comprising a first plurality of objects of the abstraction layer is received, the query is transformed to a query state based on the second metadata of the abstraction layer, and a result set is acquired from the dataset using the query state and the analysis cube.
摘要翻译：一种计算机实现的系统，用于接收用于初始化与分析立方体和数据集相关联的数据提供者的指令，并且响应于该指令获取与分析多维数据集相关联的第一元数据，并基于第一元数据生成第二元数据包括多个对象的抽象层。接收到包括抽象层的第一多个对象的查询，基于抽象层的第二元数据将查询转换为查询状态，并且使用查询状态和分析立方体从数据集获取结果集。

2. 发明授权

EP3035211B1 VISUALIZING LARGE DATA VOLUMES UTILIZING INITIAL SAMPLING AND MULTI-STAGE CALCULATIONS 有权
公开(公告)号：EP3035211B1
公开(公告)日：2018-10-03
申请号：EP15003481.7
申请日：2015-12-07
申请人： Business Objects Software Ltd.
发明人： Naibo, Alexis , Xue, Xiaohui , Le Biannic, Yann
IPC分类号： G06F17/30
CPC分类号： G06F17/30306 , G06F17/30345 , G06F17/30572 , G06F17/30991
摘要： Embodiments visualize large data volumes utilizing initial sampling to reduce size of a dataset. This sampling may be random in nature. The sampled dataset may be refined (wrangled) by binning, grouping, cleansing, and/or other techniques to produce a wrangled sample dataset. A user defines useful end visualization(s) by inputting expected dimension/measures. From these visualizations of sampled data, minimal grouping sets are deduced for application to the full dataset. The user publishes/schedules the wrangled operation and grouping sets definition. Based on this, a wrangled dataset and grouping sets are produced in the big data layer. When the user accesses the visualization(s), minimal grouping sets are retrieved in the in-memory engine of the client and processed by an in-memory database engine according to the common processing plan. This produces result sets and a final set of visualizations of the full dataset, in which the user can recognize valuable data trends and/or relationships.

3. 发明公开

EP3035211A1 VISUALIZING LARGE DATA VOLUMES UTILIZING INITIAL SAMPLING AND MULTI-STAGE CALCULATIONS 有权
标题翻译：可视化大量数据使用首件检验和多级演算
公开(公告)号：EP3035211A1
公开(公告)日：2016-06-22
申请号：EP15003481.7
申请日：2015-12-07
申请人： Business Objects Software Ltd.
发明人： Naibo, Alexis , Xue, Xiaohui , Le Biannic, Yann
IPC分类号： G06F17/30
CPC分类号： G06F17/30306 , G06F17/30345 , G06F17/30572 , G06F17/30991
摘要： Embodiments visualize large data volumes utilizing initial sampling to reduce size of a dataset. This sampling may be random in nature. The sampled dataset may be refined (wrangled) by binning, grouping, cleansing, and/or other techniques to produce a wrangled sample dataset. A user defines useful end visualization(s) by inputting expected dimension/measures. From these visualizations of sampled data, minimal grouping sets are deduced for application to the full dataset. The user publishes/schedules the wrangled operation and grouping sets definition. Based on this, a wrangled dataset and grouping sets are produced in the big data layer. When the user accesses the visualization(s), minimal grouping sets are retrieved in the in-memory engine of the client and processed by an in-memory database engine according to the common processing plan. This produces result sets and a final set of visualizations of the full dataset, in which the user can recognize valuable data trends and/or relationships.
摘要翻译：实施例可视化大量数据利用初始采样，以减少的数据集的大小。这种采样的性质可以是随机的。所采样的数据集可被细化（口角）通过分级，分组，清洗，和/或其它技术，以产生口角样本数据集。用户通过输入预期尺寸/措施定义有用的最终可视化（多个）。从采样数据的可视化的论文，最少的分组集推导出应用到全部数据集。所述用户发布/调度口角业务和分组集定义。基于此，一个数据集口角，在大数据层中产生的分组集。当用户访问的可视化（S），在客户机的存储器内发动机被检索并通过内存数据库引擎gemäß处理以共同的处理计划最小分组集。这将产生结果集和最后一组完整的数据集，其中用户可以识别有价值的数据趋势和/或关系的可视化。

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