A method may include generating, based on a representation of a hierarchy stored in a database, a visiting sequence data structure. The hierarchy may be stored in a table in the database. Each of a plurality of rows comprising the table may correspond to one of a plurality of nodes comprising the hierarchy. The visiting sequence data structure may include a row vector specifying an order for traversing the plurality of nodes in the hierarchy. A hierarchical window function may be executed by iterating through the plurality of rows in the table in accordance with the order specified by the row vector. The execution of the hierarchical window function may further include determining, for a first node in the hierarchy, a summary value corresponding to a first value of the first node and a second value of a second node descendent from the first node.

A system (100) for Partial Unstructured Information Processing, constituting storing, indexing, querying and retrieval of partially specified unstructured data, the system (100) comprising: Quantum Clustering Algorithm (101) that partitions data records in different clusters such that the data in each cluster can be indexed efficiently, a Compressed Ternary Tree (111, 112, 113) that replaces all conceivable indices for each cluster thereby solving the Unthinkable Query Problem (110) for each cluster, and a Virtual Query Processor (120) that converts traditional data base queries to raw Compressed Ternary Tree queries and appropriate filters (121, 122, 123).

A query requesting a count of unique data values for a specific attribute is received. The received query is used to generate and transmit a plurality of non-overlapping queries to a data store. A plurality of responses is received from the data store. Results from the plurality of responses is summed and the resulting sum is returned.

In a pipeline of operations having a terminating operation and a source operation, a builder is built corresponding to the terminating operation. The builder may also correspond to one or more intermediate operations. A database query is generated corresponding to the builder and is sent to a database or a data source for efficient access to the database.

Supervised partitioning is used to perform record matching. A request to identify matches between records is received. A graph representation that indicates similarities between the records is partitioned and an evaluation of the partitioning is performed according to a supervised machine learning technique to generate a confidence value in the partitioning. An indication of equivalent records according to the partitioning and the confidence value of the partitioning may be provided.

An analytics engine (AE) computing system for analyzing and evaluating data in real-time associated with a performance of parties interacting within a multi-party interaction is provided. The AE system is configured to receive interaction data from a data validation (DV) computing device, retrieve contextual data from a contextual data source, determine a task identifier, and calculate a task score. The AE system is also configured to retrieve normalization model data from a normalization database, compare a plurality of normalization rules to the validated interaction data and the contextual data, and determine at least one normalization factor applies to the task score. The AE system is further configured to normalize the task score based on the at least one normalization factor, calculate an aggregate score using the normalized task score, and store the validated interaction data, the normalized task score, and the aggregate score in an analysis database.

Aspects of the disclosure relate to transforming data structures and data objects. A computing platform may query a logical view of a data table associated with a first database maintained by a first database server in a first schema and may receive source data associated with the logical view. Subsequently, the computing platform may split the source data into a plurality of data chunks associated with the logical view. Next, the computing platform may move the plurality of data chunks to a plurality of nodes configured to receive and transform the plurality of data chunks from the first schema to a second schema different from the first schema. Then, the computing platform may command the plurality of nodes to transform the plurality of data chunks and may move the transformed data from the plurality of nodes to a second database maintained by a second database server in the second schema.

Systems and methods are disclosed for processing and executing queries against one or more dataset. As part of processing the query, the system determines whether the query is susceptible to a significantly imbalanced partition. In the event, the query is susceptible to an imbalanced partition, the system monitors the query and determines whether to perform a multi-partitioning determination to avoid a significantly imbalanced partition.

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.