In accordance with an embodiment, described herein are systems and methods for enabling multiple parents with weights in a multidimensional database. An exemplary system can comprise a computer that includes one or more microprocessors, and a multidimensional database server executing on the computer, wherein the multidimensional database server supports at least one hierarchical structure of data dimensions. A data dimension can comprises a plurality of members, a first set of members being a first level, and a second set of members being at a second level. A member of the second set of members at the second level can comprises two or more member-member relationships with two or more members of the first set of members at the first level. Each of the two or more member-member relationships are associated with a weight.

Data processing method organizing and processing data in a distributed computing system. By organizing select/secret content with [enterprise and external designated] categorical filters (content, contextual and taxonomic) to create further search terms for data mining both enterprise and external data sources (databases, data collections, data stores). The result being aggregated select/secret content. The aggregated select/secret content is stored in the corresponding select/secret content data store. The aggregated select/secret content is further processed for convergent or divergent characteristics. By identifying unknown data elements, another search gathers supplemental documents. Data element ranges are set by taxonomic filter and said contextual filters. Relevancy factors are identified by relationship between input and supplemental documents. Search is controlled by user selection, continuous search, iterative search (n cycles), search within m search terms, and search time.

Methods and apparatus are disclosed for representing a dynamic hierarchical system as a composite graph data structure. Members of a system are represented as primary nodes of a tree. Multiple system states have respective trees, which can be overlaid to obtain a composite graph. The composite graph can be augmented with secondary nodes for member attributes, and further nodes for state-dependent values of the attributes. Methods of processing bottom-up, top-down, and filtered queries are disclosed. Applications to military, manufacturing, and communication networks are provided.

Presented herein are methods of replicating versioned and hierarchical data structures, as well as data structures representing complex transactions. Due to interdependencies between data entities and a lack of guaranteed message ordering, simple replication methods employed for simple data types cannot be used. Operations on data structures exhibit dependencies between the messages making up the operations. This strategy can be extended to various types of complex transactions by considering certain messages to depend on other messages or on the existence of other entries at the data store. Regardless of origin, these dependencies can be enforced by suspending the processing of messages with unsatisfied dependencies until all of its dependencies have been met. Alternately, transactions can be committed immediately, creating entities that include versioned identifiers for each of their dependencies. These entities can then be garbage collected of the parent objects are not subsequently created.

Disclosed are various examples of integrating multiple domains within a directory service. A computing device retrieves a first list of members in a first group of users for the domain from a first directory service for a first domain. The computing device then determines that a second group of users is a member of the first group of users, wherein the second group of users corresponds to a second domain. The computing device then retrieves a second list of members in the second group of users from a second directory service for a second domain. The computing device subsequently compares the first list of members in the first group of users and the second list of members in the second group of users with a third list of members in a third group of users, wherein the third list of members in the third group of users corresponds to a user list maintained by the application. The computing device then adds to the third list of members in the third group of users each user that is both present in the first list of members in the first group of users or in the second list of members in the second group of users and missing from the third list of members in the third group of users.

Techniques and structures to synchronize hierarchical data, comprising. A conflict between data stored at a computing device and data stored at a service provider database is detected. A synchronization operation is performed to synchronize a plurality of objects within the hierarchical entity data stored at the computing device with hierarchical entity data stored at the service provider database.

Data cataloging has become a necessity for empowering organizations with analytical ability. Conventional cataloging systems may fail to provide proper visualization of data to the different stakeholders of an organization. The present disclosure provides a hierarchical dynamic cataloging system so that visualization of data at different levels would be possible for different stake holders. In the present disclosure, a hierarchical structure of algorithms and multiple stake holders along with relevant metadata is generated. Further, a catalog is generated by performing a mapping across components comprised in the hierarchical structure and identifying relationship across the components based on mapping. The catalog gets dynamically updated and provides a dynamic view of the algorithms and associated metadata to the multiple stakeholders of an organization. Further, the disclosure supports reuse of already developed algorithms across multiple applications and domains resulting in optimization of resources and time.

Methods and systems for searching directory access groups are disclosed. A set of groups associated with a logon user is determined. The set of groups is partitioned into one or more disjoint subsets, wherein each of the disjoint subsets is represented by a data representation including a root node and one or more intermediate nodes. For each of the disjoint subsets, the disjoint subset is path compressed to flatten a structure of the data representation representing the disjoint subset. The data representation is cached to a database cache.

The present approach relates generally to systems and methods for outputting metric data from resources with a database accessible by a client instance. The client instance is hosted by one or more data centers and accessible by one or more remote client networks. In accordance with the present approach, a request to track metric data related to a resource is received. Further, a configuration item (CI) is retrieved from a database accessible by the client instance based at least in part on data associated with the request. Further, a type of CI is identified. Even further, a resource type associated with the type of the CI is identified based at least in part on a resource abstraction layer accessible by the client instance. Further still, the resource type is linked to the resource table and metric data associated with the resource is outputted.

A method receives data from a data source. The method generates a plurality of generalizations of the data. The method sends the plurality of generalizations of the data to a plurality of execution nodes, wherein each of the plurality of execution nodes includes computational resources to compute a candidate generalization using an information loss scoring function. The method receives a candidate generalization from each of the plurality of execution nodes. The method selects a preferred generalization from the plurality of candidate generalizations. The method generates an anonymized view of the data set using the preferred generalization.