A method, an apparatus, and a system for configuring, designing, and/or implementing database tables are detailed that provides a framework into which a remainder of database tables is developed. Also detailed is a method to develop this framework of database tables. This so developed framework provides a platform for converting multiple independent heterogeneous databases into standardized homogeneous databases.

A data model identifying a first and second table may be stored, the first table comprising a first and second attribute, the second table comprising a third attribute. A first filter parameter of a first filter and a second filter parameter of a second filter may be obtained. A first tag value may be associated with the first and second filters. A set of filters including the first and second filters may be determined in response to a determination that the first and second filters are associated with the first tag value. An argument indicating the first and second filter parameters may be generated based on the set of filters. A call to the first table may be executed based on the argument, the execution of the call causing values of the first and second attributes to be obtained based on the first and second filter parameters.

A system for efficiently parsing semi-structured deep packet inspection traffic data tied to a telecommunications entity. The system comprises a computing device having access to a user activity data source and is configured to progressively accumulate a plurality of incoming usage activity data into a plurality of hypercubes, classify streaming data on-the-fly into multiple grades, route it to an appropriate next stage of processing, numerically factorize it to enable drilldown to individual subscriber data, and organize into layouts for efficient data processing, anomaly detection, and subsequent access/investigation. A computerized method for performing the same.

A data pre-processing architecture may include an interface and a pruning logic configured to receive, via the interface, at least one filter value from a query processor; use the at least one filter value to scan rows or columns of a data table stored in a memory; generate a selection indicator identifying a set of rows or columns of the data table where the at least one filter value resides; and provide to the query processor a filtered output based on the selection indicator.

Methods and systems for governing execution of a geography dependent computer process are provided. In one aspect, a method includes receiving a target location comprising a geographic identifier. The method also includes accessing a data store comprising a plurality of maps. Each map of the plurality of maps includes a plurality of geometric shapes and each geometric shape is associated with an execution rule. The method also includes determining which geometric shape of the plurality of geometric shapes the geographic identifier is bounded within for at least two maps of the plurality of maps. The method further includes generating an aggregate rule set based on each execution rule associated with each geometric shape determined to bound the geographic identifier. The method further includes applying the aggregate rule set. Machine-readable media are also provided.

A computing device receives user input to specify a natural language command directed to a data source. In accordance with the user input, the device forms an intermediate expression according to a context-free grammar and a semantic model of data fields in the data source. The natural language command includes (i) a first term that specifies an aggregation type in a first aggregation, (ii) a second term that specifies a data field, in the semantic model, to be aggregated for the first aggregation, and (iii) terms that specify data fields, in the semantic model, to determine grouping for the first aggregation. The device translates the intermediate expression into database queries, executes the database queries to retrieve one or more data sets from the data source, aggregated according to the first aggregation, then generates and displays a data visualization of the retrieved data sets.

A system and computer implemented method for execution of aggregation expressions on a distributed non-relational database system is provided. The method comprises the acts of determining, by a computer system, an optimization for execution of an aggregation operation, wherein the aggregation operation includes a plurality of data operations on a distributed non-relational database; modifying, by the computer system, the plurality of data operations to optimize execution; splitting the aggregation operation into a distributed aggregation operation and a merged aggregation operation; instructing each of a plurality of shard servers to perform the distributed aggregation operation; aggregating, at a merging shard server, the results of the distributed aggregation operation from each of the plurality of shard servers; and performing the merged aggregation operation on the aggregated results of the distributed aggregation operation from each of the plurality of shard servers.

A method of processing event data, a device, and a medium are provided, which relate to fields of deep learning, natural language processing, cloud services, etc. The method of processing event data includes: determining target feature data corresponding to target event data, in response to receiving a query request containing the target event data; selecting correlated feature data from candidate feature data based on the target feature data, wherein a similarity between the correlated feature data and the target feature data meets a preset similarity condition; determining operation data associated with the correlated feature data, wherein the operation data represents a level of attention to correlated event data corresponding to the correlated feature data; and determining a level of attention to the target event data based on the operation data.

In examples, streaming data is received from a data source (e.g., by an edge device associated with a data platform) and is queued and aggregated. Batch data may similarly be received from a data source. The batch data and the aggregated streaming data may be processed to generate metadata accordingly. The data and metadata may be provided to the data platform, where the metadata may be used to update an index and the data may be stored in association with the index. In some instances, the data may be stored in chunks to facilitate subsequent retrieval of the data. In response to a request for the data, the index may be used to identify relevant data, which may include data associated with batch and/or streaming data formats, thereby enabling the client device to access data having any of a variety of formats from the data platform.

Systems and methods for controlling data in a hierarchy receive a data query corresponding to data organized within nodes in a data hierarchy, wherein the data hierarchy is defined by a plurality of dimensions. A data traversal of the data hierarchy is performed including a rollup operation between different nodes at different levels of the plurality of dimensions. The rollup operation aggregates data values of the nodes at the different levels. Aggregated values for different nodes at each level are output based on the rollup operation, and the data query is executed using the aggregated values for the different nodes.