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    • 9. 发明授权
    • Event-based database access execution
    • 基于事件的数据库访问执行
    • US07120635B2
    • 2006-10-10
    • US10319980
    • 2002-12-16
    • Manish Anand BhideMukesh Kumar Mohania
    • Manish Anand BhideMukesh Kumar Mohania
    • G06F17/30
    • G06F21/6218G06F2216/03G06F2221/2101G06F2221/2145Y10S707/99932Y10S707/99936Y10S707/99939Y10S707/99942
    • An authorisation privilege for an access request is inferred when no explicit privilege exists. The inference can be performed by way of mining occurrence patterns or derived from user hierarchy, profile, click history, transaction history or role. For any access request, the respective explicit privilege or inferred privilege is verified by the database or security administrator before the access request is permitted. Conditions expressed in an access policy are evaluated on the occurrence of predefined events. The events extend beyond user access requests, and include external events, composite events and access of a referential type. The access policy is framed in ‘event, condition, access enforcement’ terminology. The access control rules can be parameterised and can be instantiated by data obtained from inference rules associated with the conditions of the policy. The conditions have an evaluation component and an inference component. The access privileges supported are: read, write and indirect read. An indirect read operation typically allows a user qualified access to one or more portions of a database, but not the entire database.
    • 当没有显式权限时,会推断访问请求的授权权限。 推理可以通过采矿发生模式或从用户层次结构,配置文件,点击历史记录,交易历史或角色导出来执行。 对于任何访问请求,在允许访问请求之前,数据库或安全管理员对相应的显式权限或推断权限进行验证。 在访问策略中表达的条件是根据预定义事件的发生进行评估的。 这些事件超出了用户访问请求,并且包括外部事件,复合事件和引用类型的访问。 访问策略是在“事件,条件,访问实施”术语中构成的。 访问控制规则可以被参数化,并且可以通过从与策略的条件相关联的推理规则获得的数据来实例化。 条件具有评估组件和推理组件。 支持的访问权限是:读,写和间接读取。 间接读取操作通常允许用户对数据库的一个或多个部分进行合格访问,但不允许整个数据库。
    • 10. 发明申请
    • DATA WAREHOUSE DATA MODEL ADAPTERS
    • 数据仓库数据模型适配器
    • US20120054249A1
    • 2012-03-01
    • US12868363
    • 2010-08-25
    • Vishal Singh BatraManish Anand BhideMukesh Kumar MohaniaSumit Negi
    • Vishal Singh BatraManish Anand BhideMukesh Kumar MohaniaSumit Negi
    • G06F7/00
    • G06F17/30592
    • In the context of data administration in enterprises, an effective manner of providing a central data warehouse, particularly via employing a tool that helps by analyzing existing data and reports from different business units. In accordance with at least one embodiment of the invention, such a tool analyzes the data model of an enterprise and proposes alternatives for building a new data warehouse. The tool, in accordance with at least one embodiment of the invention, models the problem of identifying fact/dimension attributes of a warehouse model as a graph cut on a Dependency Analysis Graph (DAG). The DAG is built using existing data models and the report generation scripts. The tool also uses the DAG for generation of ETL (Extract, Transform Load) scripts that can be used to populate the newly proposed data warehouse from data present in the existing schemas.
    • 在企业数据管理的背景下,提供中央数据仓库的有效方式,特别是通过采用帮助分析不同业务部门的现有数据和报告的工具。 根据本发明的至少一个实施例,这种工具分析企业的数据模型并提出了构建新的数据仓库的替代方案。 根据本发明的至少一个实施例,该工具将识别仓库模型的事实/维度属性的问题模型化为在依赖关系分析图(DAG)上切割的图形。 DAG使用现有的数据模型和报告生成脚本构建。 该工具还使用DAG生成ETL(提取,转换加载)脚本,可用于根据现有模式中存在的数据填充新提出的数据仓库。