Abstract: The presently disclosed subject matter includes a system and method of managing computer memory of a column-oriented database, which enables to reduce the tradeoff between eviction and recycling of intermediate query results and thus retain much of the recycling capability at a considerably lower computer memory cost. The computer memory comprises one or more intermediates, each intermediate being generated by execution of a respective instruction, the instruction being part of a given query. An hierarchical data-structure is generated and stored in the computer memory, wherein different nodes in the hierarchical data-structure represent different respective intermediates stored in the computer memory. Responsive to a delete command, the at least one intermediate is deleted from the computer memory, while a respective node representing the at least one intermediate is maintained in the hierarchical data-structure.

Abstract: A system and method for generating training sets for training neural networks. The method includes receiving a plurality of query pairs, wherein each of the plurality of query pairs includes a query and a real result previously determined for the query; determining at least one variable element of each query in the plurality of received query pairs; determining a variance for the at least determined variable element of each query in the plurality of received query pairs; and generating a training set based on the determined variable element, the determined variance, and the previously determined real result.

Abstract: A system and method for providing query responses from a big data system utilizing a knowledge graph is presented. The method includes generating a plurality of local knowledge graphs, each local knowledge graph of the plurality of local knowledge graphs generated respective of a unique plurality of data sources; generating a universal knowledge graph based on the generated plurality of local knowledge graphs; fine-tuning a large language model (LLM) based on the generated universal knowledge graph; receiving a query directed at a data source of the plurality of unique data sources of a first local knowledge graph; generating a prompt for the LLM based on the received query; and processing the prompt utilizing the LLM to generate an output, wherein the output is a response to the received query.

Abstract: A method and system for improving cache efficiency is presented. The method includes determining a cachability relevance score for each query node of a plurality of query nodes from a semantic knowledge graph; selecting at least one cacheable query node of the plurality of query nodes based on the cachability relevance score of the at least one cacheable query node; storing in a cache a result of executing a query generated based on the at least one cacheable query node; and generating a query execution plan based on the at least one cacheable query node, wherein the generated query execution plan includes at least one instruction for query execution using the stored result; and executing the generated query execution plan.

Abstract: A system and method for improving cache efficiency. A method includes selecting at least one cacheable query node of a plurality of query nodes from a semantic knowledge graph, wherein the semantic knowledge graph includes the plurality of query nodes and a plurality of edges, each edge connecting two of the plurality of query nodes and having a connecting score, wherein the connecting score of each edge indicates a strength of relationship between the two nodes connected by the edge; storing a result of executing a query generated based on the at least one cacheable query node in a cache; and generating a query execution plan based on the at least one cacheable query node, wherein the generated query execution plan includes at least one instruction for query execution using the stored result.

Abstract: A system and method for improving training of a recurrent neural network (RNN) to provide a response to a table-based database query is presented. The method includes: receiving a plurality of query pairs, each including a database query and a response, the response generated by executing the database query on a database; detecting a variable in each query; determining a variance of the variable; generating a subset of potential values for the detected variable based on the determined variance, wherein each potential value is different from the response of each query pair; generating a plurality of training queries, each training query based on a database query of a query pair of the plurality of query pairs and a corresponding potential value from the first subset; executing each training query to generate a training response; and training the RNN based on the plurality of training queries and a corresponding training response.

Abstract: A system and method for providing local approximations of query results are provided. The method includes querying a primary neural network with at least one test query, wherein the at least one test query includes a real test result derived from executing the at least one training query on a data set; receiving from the primary neural network a predicted test result in response to the at least one test query; sending, based on the predicted test result, a model of a primary neural network to a local machine; and storing the model of a local neural network of the local machine, wherein the local neural network is configured to generate a prediction in response to a user query received by the local machine.

Abstract: A system and method for displaying data using temporal granularities. The method includes determining at least one first dataset of a plurality of datasets based on at least one temporal data requirement, wherein the plurality of datasets is generated based on a data model, wherein each of the plurality of datasets is generated based further on a distinct temporal granularity of a plurality of temporal granularities, wherein the distinct temporal granularity of each of the at least one first dataset meets at least one of the at least one temporal data requirement; and querying the determined at least one first dataset in order to obtain at least one query result.

Abstract: A system and method for providing an improved user interface for executing data operations. A method includes: identifying a first node and a second node from different connections graphs, each node representing a respective user account, the user accounts of the first and second nodes sharing at least one common attribute; generating, based on the different connections graphs, an influence indicator for each of the first node and the second node; identifying a data operation executed by the first node on a dataset when the influence indicator of the first node is higher than the influence indicator of the second node, wherein the identified data operation causes generation or retrieval of business intelligence system data when executed; and sending data indicating the identified data operation to a device of the second node, wherein the device is configured to display a user interface including the identified data operation.

Abstract: A system and method for generating data visualizations. The method includes generating an enriched data layer based on a plurality of knowledge graphs, the plurality of knowledge graphs including a plurality of first nodes, the enriched data layer including a plurality of second nodes, wherein each of the plurality of second nodes is connected via an edge to at least one of the plurality of first nodes; and generating a data visualization based on the enriched data layer and a request for data, wherein the request for data indicates a type of data corresponding to at least one of the plurality of second nodes, wherein the data visualization is generated using data represented by at least one of the plurality of first nodes connected to the at least one of the plurality of second nodes.

Abstract: A system and method for providing visual data for user interfaces based on a knowledge graph. A method includes identifying at least one second node with respect to a first node based on connections between nodes of a knowledge graph, wherein the knowledge graph includes the first node and the at least one second node, wherein the first node represents a dimension of interest; selecting at least one third node from among the at least one second node by determining a correlation between the first node and each of the at least one second node; determining a new value for a dimension of each of the at least one third node based on a target value such that the correlation of the third node to the first node is maintained while achieving the target value; and generating visual data for an action item user interface based on the new values.

Abstract: A system and method for generating a semantic graph. The method includes: parsing each of a plurality of events into a plurality of objects, wherein the plurality of events includes a plurality of queries, wherein each event of the plurality of events is related to an interaction with at least one data source; determining, for each of the plurality of events, a relationship between two objects of the plurality of objects; and generating a semantic knowledge graph based on the determined relationships, the semantic knowledge graph including a plurality of query nodes and a plurality of edges, wherein each query node corresponds to a respective object of the plurality of objects, wherein each query node is connected to another query node of the plurality of query nodes by one of the plurality of edges, wherein each edge represents a relationship between the objects connected by the edge.

Abstract: A system and method for accelerating relational functions between tables. The method includes: determining a plurality of first index values for a plurality of first unique keys in a first column of a first table; determining a plurality of second index values for a plurality of second unique keys in a second column of a second table; generating a hashed third table based on the first column of the first table and the plurality of first index values; generating a hashed fourth table based on the second column of the first table and the plurality of first index values; and generating a fifth table by performing a JOIN operation between the third table and the fourth table based on at least one third column, wherein each of third column includes a plurality of third unique keys that are common between the third table and the fourth table.

Abstract: A system and method for partitioning data based on authorization rules. The method includes initiating a plurality of data nodes, each data node including a dataset generated based on a shared data model, wherein each of the plurality of data nodes corresponds to at least one authorization rule, wherein each authorization rule authorizes at least one user identifier to access a respective data node of the plurality of data nodes; and configuring an extract, transform, and load (ETL) application service to extract data from a data source and to load data from the data source to the dataset stored on a first data node of the plurality of data nodes when the at least one first authorization rule authorizes a requesting user to access the first data node.

Abstract: A system and method for displaying data using temporal granularities. The method includes determining at least one first dataset of a plurality of datasets based on at least one temporal data requirement, wherein the plurality of datasets is generated based on a data model, wherein each of the plurality of datasets is generated based further on a distinct temporal granularity of a plurality of temporal granularities, wherein the distinct temporal granularity of each of the at least one first dataset meets at least one of the at least one temporal data requirement; and querying the determined at least one first dataset in order to obtain at least one query result.

Abstract: A method, computer system and computer program product, the method comprising: upon receiving a database query comprising at least a first and a second join operations: storing the database query in the memory; identifying by the processor within the database query the first join operation, wherein the first join operation is a many-to-many join operation or a one-to-many join operation between a first table and a second table, in which fields of the second table are used only for filtering rows from the first table or for joining with another table; and converting by the processor the first join operation to an enhanced operation which eliminates returning at least two matches for at least one row from the first table when the database query is executed.

Abstract: A system and method for partitioning data based on authorization rules. The method includes initiating a plurality of data nodes, each data node including a dataset generated based on a shared data model, wherein each of the plurality of data nodes corresponds to at least one authorization rule, wherein each authorization rule authorizes at least one user identifier to access a respective data node of the plurality of data nodes; and configuring an extract, transform, and load (ETL) application service to extract data from a data source and to load data from the data source to the dataset stored on a first data node of the plurality of data nodes when the at least one first authorization rule authorizes a requesting user to access the first data node.

Abstract: A system and method for displaying data using temporal granularities. The method includes determining at least one first dataset of a plurality of datasets based on at least one temporal data requirement, wherein the plurality of datasets is generated based on a data model, wherein each of the plurality of datasets is generated based further on a distinct temporal granularity of a plurality of temporal granularities, wherein the distinct temporal granularity of each of the at least one first dataset meets at least one of the at least one temporal data requirement; and querying the determined at least one first dataset in order to obtain at least one query result.

Abstract: A method, computer system and computer program product, the method comprising: upon receiving a database query comprising at least a first and a second join operations: storing the database query in the memory; identifying by the processor within the database query the first join operation, wherein the first join operation is a many-to-many join operation or a one-to-many join operation between a first table and a second table, in which fields of the second table are used only for filtering rows from the first table or for joining with another table; and converting by the processor the first join operation to an enhanced operation which eliminates returning at least two matches for at least one row from the first table when the database query is executed.

Abstract: A system and method for providing sensory analytics responses. The method comprises collecting raw data from a plurality of data sources; extracting, from the collected raw data, a subset of the raw data to be analyzed; generating, based on the extracted subset of the raw data, an analytics dataset, wherein the analytics dataset includes a performance indicator; determining, based on at least one received input, at least one query; determining, based on the generated analytics dataset, a response to the at least one query, wherein the response includes at least one sensory output; and causing projection of the determined at least one sensory output.