Abstract: A computing device may receive a natural language query. The computing device may determine, based on the natural language query, a set of search criteria. The computing device may determine, from a plurality of data sets, two or more data sets that are relevant to the natural language query based at least in part on matches between the set of search criteria and attributes of the plurality of data sets. The computing device may join the two or more data sets, including joining one or more rows and one or more columns of the two or more data sets to produce a joint data set. The computing device may output a representation of the joint data set.

Abstract: A computing device receives a natural language query. The computing device determines, based on the natural language query, a set of search criteria. The computing device determines, from a plurality of data sets, two or more data sets that are relevant to the natural language query based at least in part on matches between the set of search criteria and attributes of the plurality of data sets. The computing device joins the two or more data sets, including joining one or more rows and one or more columns of the two or more data sets to produce a joint data set. The computing device outputs a representation of the joint data set.

Abstract: Techniques are described for modeling information from a data source. In one example, a method for modeling information from a data source includes comparing, with one or more computing devices, a data item heading from the data source with concept keywords in a concept library, the concept library comprising a plurality of concepts and one or more of the concept keywords in at least one language associated with each of one or more of the concepts. The method further includes identifying, with one or more computing devices, one or more matches between the data item heading and one or more concept keywords associated with a particular concept from among the concepts comprised in the concept library. The method further includes identifying, with one or more computing devices, the data item heading as being associated with the particular concept.

Abstract: Techniques are described for modeling information from a data source. In one example, a method for modeling information from a data source includes comparing, with one or more computing devices, a data item heading from the data source with concept keywords in a concept library, the concept library comprising a plurality of concepts and one or more of the concept keywords in at least one language associated with each of one or more of the concepts. The method further includes identifying, with one or more computing devices, one or more matches between the data item heading and one or more concept keywords associated with a particular concept from among the concepts comprised in the concept library. The method further includes identifying, with one or more computing devices, the data item heading as being associated with the particular concept.

Abstract: A processor-implemented method retrieves information from a database system. A data query, which includes a specification of information to be retrieved from the database system, is generated. A first parameter specifying a condition to be met by the retrieved information is defined. A second parameter specifying one or more data reduction operations to be executed if the condition defined by the first parameter is not met is defined. The generated data query and the first and second parameters are then transmitted to the database system.

Abstract: A computing device may receive a natural language query. The computing device may determine, based on the natural language query, a set of search criteria. The computing device may determine, from a plurality of data sets, two or more data sets that are relevant to the natural language query based at least in part on matches between the set of search criteria and attributes of the plurality of data sets. The computing device may join the two or more data sets, including joining one or more rows and one or more columns of the two or more data sets to produce a joint data set. The computing device may output a representation of the joint data set.

Abstract: A computing device may receive a natural language query. The computing device may determine, based on the natural language query, a set of search criteria. The computing device may determine, from a plurality of data sets, two or more data sets that are relevant to the natural language query based at least in part on matches between the set of search criteria and attributes of the plurality of data sets. The computing device may join the two or more data sets, including joining one or more rows and one or more columns of the two or more data sets to produce a joint data set. The computing device may output a representation of the joint data set.

Abstract: Provided are techniques for processing a multidimensional query. For each multidimensional expression in the multidimensional query, the multidimensional expression is evaluated to generate a representation that includes an evaluation context, a degeneration status, and condensed value storage that does not store data that would be replicated due to degeneration, and the representation is stored.

Abstract: Embodiments of the present invention disclose a method, computer program product, and system for determining recommendations in data analysis. A computer identifies an analysis step currently being performed in a data analysis. The computer identifies data points corresponding to the identified analysis step currently being performed and one or more previous analyses. The computer determines a distance between the data points corresponding to the identified analysis step currently being performed and each of the one or more previous data analyses utilizing a distance computing algorithm. The computer determines a ranking of the one or more previous data analyses corresponding to the determined distances between the data points corresponding to the identified analysis step currently being performed and each of the one or more previous data analyses.

Abstract: Embodiments of the present invention disclose a method, computer program product, and system for determining recommendations in data analysis. A computer identifies an analysis step currently being performed in a data analysis. The computer identifies data points corresponding to the identified analysis step currently being performed and one or more previous analyses. The computer determines a distance between the data points corresponding to the identified analysis step currently being performed and each of the one or more previous data analyses utilizing a distance computing algorithm. The computer determines a ranking of the one or more previous data analyses corresponding to the determined distances between the data points corresponding to the identified analysis step currently being performed and each of the one or more previous data analyses.

Abstract: Techniques are described for modeling information from a data source. In one example, a method for modeling information from a data source includes comparing, with one or more computing devices, a data item heading from the data source with concept keywords in a concept library, the concept library comprising a plurality of concepts and one or more of the concept keywords in at least one language associated with each of one or more of the concepts. The method further includes identifying, with one or more computing devices, one or more matches between the data item heading and one or more concept keywords associated with a particular concept from among the concepts comprised in the concept library. The method further includes identifying, with one or more computing devices, the data item heading as being associated with the particular concept.

Abstract: Techniques are described for modeling information from a data source. In one example, a method for modeling information from a data source includes identifying one or more lexical clues associated with each of one or more data item headings from the data source based on a set of lexical clue detection rules. The method further includes mapping each of one or more of the data item headings to one or more business concepts based on comparing the one or more identified lexical clues associated with each of one or more of the data item headings with a business ontology that comprises a description of the business concepts. The method further includes generating a semantic business intelligence model comprising one or more semantic associations between the one or more data item headings based on the mapping of the data item headings to the one or more of the business concepts.

Abstract: Techniques of the disclosure may include a method comprising receiving a first request for a recommendation to configure input data for output, determining, based at least in part upon templates, an object class corresponding to the first request, determining, based at least in part on input data and the templates, one or more output objects and one or more scores, wherein the output objects comprise configurations of the input data for the determined object class, and where each of the output objects is associated with a score. The method may further comprise outputting a indication of the output objects having an associated score that exceeds a specified threshold value, responsive to receiving a second request to resolve a specified output object, determining, based at least in part on the one or more templates and the second request, a resolved output object and outputting an indication of the resolved output object.

Abstract: A processor-implemented method retrieves information from a database system. A data query, which includes a specification of information to be retrieved from the database system, is generated. A first parameter specifying a condition to be met by the retrieved information is defined. A second parameter specifying one or more data reduction operations to be executed if the condition defined by the first parameter is not met is defined. The generated data query and the first and second parameters are then transmitted to the database system.

Abstract: A secure caching system and caching method include receiving a user request for data, the request containing a security context, and searching a cache for the requested data based on the user request and the received security context. If the requested data is found in cache, returning the cached data in response to the user request. If the requested data is not found in cache, obtaining the requested data from a data source, storing the obtained data in the cache and associating the obtained data with the security context, and returning the requested data in response to the user request. The search for the requested data can include searching for a security list that has the security context as a key, the security list including an address in the cache of the requested data.

Abstract: Provided are techniques for processing a multidimensional query. For each multidimensional expression in the multidimensional query, the multidimensional expression is evaluated to generate a representation that includes an evaluation context, a degeneration status, and condensed value storage that does not store data that would be replicated due to degeneration, and the representation is stored.

Abstract: Techniques are described for modeling information from a data source. In one example, a method for modeling information from a data source includes comparing, with one or more computing devices, a data item heading from the data source with concept keywords in a concept library, the concept library comprising a plurality of concepts and one or more of the concept keywords in at least one language associated with each of one or more of the concepts. The method further includes identifying, with one or more computing devices, one or more matches between the data item heading and one or more concept keywords associated with a particular concept from among the concepts comprised in the concept library. The method further includes identifying, with one or more computing devices, the data item heading as being associated with the particular concept.

Abstract: Techniques are described for modeling information from a data source. In one example, a method for modeling information from a data source includes identifying one or more lexical clues associated with each of one or more data item headings from the data source based on a set of lexical clue detection rules. The method further includes mapping each of one or more of the data item headings to one or more business concepts based on comparing the one or more identified lexical clues associated with each of one or more of the data item headings with a business ontology that comprises a description of the business concepts. The method further includes generating a semantic business intelligence model comprising one or more semantic associations between the one or more data item headings based on the mapping of the data item headings to the one or more of the business concepts.

Abstract: Techniques of the disclosure may include a method comprising receiving a first request for a recommendation to configure input data for output, determining, based at least in part upon templates, an object class corresponding to the first request, determining, based at least in part on input data and the templates, one or more output objects and one or more scores, wherein the output objects comprise configurations of the input data for the determined object class, and where each of the output objects is associated with a score. The method may further comprise outputting a indication of the output objects having an associated score that exceeds a specified threshold value, responsive to receiving a second request to resolve a specified output object, determining, based at least in part on the one or more templates and the second request, a resolved output object and outputting an indication of the resolved output object.

Abstract: An enterprise business intelligence system includes a data access service. In one example, a method comprises receiving, with a data access service, a query and a report specification from an application, wherein the data access service is positioned between the application and a data source; creating a run tree that comprises a sequence of executable decoration nodes; executing the query on the data source, thereby providing a query result set comprising query results drawn from the data source that are responsive to the query; and executing the sequence of decoration nodes on the query result set. The decoration nodes modify the query result set, thereby producing a decorated result set based on the query result set and the decoration nodes. Producing the decorated result set comprises associating members or values in the query results with corresponding positions or calculated members in the report specification.