Abstract: The present disclosure describes methods, systems, and computer program products for providing data warehouse model federation. One computer-implemented method includes receiving a request to transform a first semantically enriched model to a second semantically enriched model, wherein the first semantically enriched model operates in a first data warehouse and the second semantically enriched model operates in a second data warehouse; identifying a set of data associated with the first semantically enriched model, wherein the set of data is stored in the first data warehouse; providing access to the set of data associated with the first semantically enriched model from the second data warehouse; creating the second semantically enriched model based on the first semantically enriched model using an interface of the second data warehouse; and deploying the second semantically enriched model in the second data warehouse.

Abstract: A computer-implemented method comprising receiving a user request. The method analyzes the data in a plurality of data sets to find inconsistent mappings. Data of data sets, such as columns formed by a join condition, are compared to determine matching or non-matching distinct characteristic values. A composite data set is generated based on the comparison. Another data set is compared with the composite data set, and the composite data set is enhanced. Each data set is compared in sequence, if the composite data set is not empty, until all data sets are analyzed. A result set is generated based on the matching or non-matching distinct characteristic values. The method may also determine if a join operates as a data filter. The operations that are used for analysis may include ‘count distinct’, ‘intersection’ and ‘Boolean operators’.

Abstract: The present disclosure describes methods, systems, and computer program products for providing data warehouse model federation. One computer-implemented method includes receiving a request to transform a first semantically enriched model to a second semantically enriched model, wherein the first semantically enriched model operates in a first data warehouse and the second semantically enriched model operates in a second data warehouse; identifying a set of data associated with the first semantically enriched model, wherein the set of data is stored in the first data warehouse; providing access to the set of data associated with the first semantically enriched model from the second data warehouse; creating the second semantically enriched model based on the first semantically enriched model using an interface of the second data warehouse; and deploying the second semantically enriched model in the second data warehouse.

Abstract: In one embodiment, a computer-implemented method comprises receiving a query. A data store stores data as a plurality of data sets. Each data set comprises a plurality of fields and a plurality of data elements. Each field is associated with a portion of data elements. The query identifies selected data sets and selected properties of the selected data sets. For each selected property, the data elements of the selected data sets associated with each selected property are determined. A first rating of the determined data elements of the selected data sets is determined based on a type of combination of a pair of selected data sets. For the selected data set pairs, a second rating of the pair is determined based on the first ratings for the selected properties. A model of a combination of the selected data sets is generated based on the second rating.

Abstract: A central data warehouse includes embedded data marts. These embedded data marts, referred to as workspaces, are assigned centrally manage data by reference only but rely directly on the centrally managed data and the underlying infrastructure. Workspaces still allow departments in an enterprise to perform certain actions on their own (like adding new data and building new models) without having to instantiate copies of the centrally managed data in a locally managed data mart.

Abstract: A system and method for uploading data from a customer system to a hosted system is disclosed. A stub is integrated with a firewall between the customer system and the hosted system. The stub includes an inbound layer on the customer system side of the firewall and an outbound layer on the hosted system side of the firewall, and the inbound layer includes a write-only directory. A demon is connected between the inbound layer and the outbound layer of the stub. The demon is configured to recognize newly received data in the write-only directory of the inbound layer, encrypt the newly received data to generate encrypted data, and move the encrypted data to the outbound layer for access by the hosted system.

Abstract: Conversion of a snowflake-like schema to a star-like schema includes a distribution of the snowflake-like schema across several host computer systems. Each host computer system has a fragment of the snowflake-like schema, including a fragment of constituent fact tables. Dimension keys in the fact table fragments are mapped to data tables via the constituent dimension tables. Data table keys are identified and populate the fact table for the converted star-like schema, thus obviating the dimension tables in the converted star-like schema.

Abstract: This disclosure provides various software and systems for efficiently maintaining aggregates. In one aspect, a system performing a computer implemented method identifies a first change to transactional data in a business application and automatically adds an aggregate record to an aggregate data structure based on the first change. The system then identifies a second change to the transactional data in the business application, the second change comprising an update to key figures associated with the first change. The system can prohibit an update to the aggregate record in the aggregate data structure based on the second change and automatically adds a second aggregate record to the aggregate data structure based on the second change to the transactional data, where the second aggregate record comprises the update to the key figures.

Abstract: In one embodiment, a computer-implemented method comprising receiving a user request. The method analyzes the data in a plurality of data sets to find inconsistent mappings. Data of data sets, such as columns formed by a join condition, are compared to determine matching or non-matching distinct characteristic values. A composite data set is generated based on the comparison. Another data set is compared with the composite data set, and the composite data set is enhanced. Each data set is compared in sequence, if the composite data set is not empty, until all data sets are analyzed. A result set is generated based on the matching or non-matching distinct characteristic values. The method may also determine if a join operates as a data filter. The operations that are used for analysis may include ‘count distinct’, ‘intersection’ and ‘Boolean operators’.

Abstract: A central data warehouse includes embedded data marts. These embedded data marts, referred to as workspaces, are assigned centrally manage data by reference only but rely directly on the centrally managed data and the underlying infrastructure. Workspaces still allow departments in an enterprise to perform certain actions on their own (like adding new data and building new models) without having to instantiate copies of the centrally managed data in a locally managed data mart.

Abstract: In one embodiment, a computer-implemented method comprises receiving a query. A data store stores data as a plurality of data sets. Each data set comprises a plurality of fields and a plurality of data elements. Each field is associated with a portion of data elements. The query identifies selected data sets and selected properties of the selected data sets. For each selected property, the data elements of the selected data sets associated with each selected property are determined. A first rating of the determined data elements of the selected data sets is determined based on a type of combination of a pair of selected data sets. For the selected data set pairs, a second rating of the pair is determined based on the first ratings for the selected properties. A model of a combination of the selected data sets is generated based on the second rating.

Abstract: Conversion of a snowflake-like schema to a star-like schema includes a distribution of the snowflake-like schema across several host computer systems. Each host computer system has a fragment of the snowflake-like schema, including a fragment of constituent fact tables. Dimension keys in the fact table fragments are mapped to data tables via the constituent dimension tables. Data table keys are identified and populate the fact table for the converted star-like schema, thus obviating the dimension tables in the converted star-like schema.

Abstract: A system and method for uploading data from a customer system to a hosted system is disclosed. A stub is integrated with a firewall between the customer system and the hosted system. The stub includes an inbound layer on the customer system side of the firewall and an outbound layer on the hosted system side of the firewall, and the inbound layer includes a write-only directory. A demon is connected between the inbound layer and the outbound layer of the stub. The demon is configured to recognize newly received data in the write-only directory of the inbound layer, encrypt the newly received data to generate encrypted data, and move the encrypted data to the outbound layer for access by the hosted system.

Abstract: This disclosure provides various software and systems for efficiently maintaining aggregates. In one aspect, a system performing a computer implemented method identifies a first change to transactional data in a business application and automatically adds an aggregate record to an aggregate data structure based on the first change. The system then identifies a second change to the transactional data in the business application, the second change comprising an update to key figures associated with the first change. The system can prohibit an update to the aggregate record in the aggregate data structure based on the second change and automatically adds a second aggregate record to the aggregate data structure based on the second change to the transactional data, where the second aggregate record comprises the update to the key figures.

Abstract: A method for estimating a runtime of a query of a data repository may abstract, extract, or otherwise generate one or more parameters of the query. Thereafter, the abstracted parameters may be associated with one or more statistical query records. From these statistical query records, a query runtime may be estimated. Related apparatuses, computer program products, and computer systems are also described.

Abstract: Methods and apparatus, including computer systems and program products, relating to an information management system and aggregating data by performing table scans. In general, in one aspect, the technique includes receiving a query for a response to a search on a database, loading data from the database into memory, filtering the data based on the query to generate a list of results, buffering at least one key figure corresponding to a result, buffering at least one dimension value corresponding to each key figure, aggregating the dimension values to generate an aggregate key, aggregating key figures corresponding to the sane aggregate key to generate one or more aggregate key figures, and displaying the response to the search on a display device. Loading the data may include compressing the data. Filtering the data may be performed blockwise.

Abstract: A first data storage schema in which a characteristic in a first dimension table is mapped by a first table and a second table can be received and a second data storage schema can be received. The first table maps the characteristic to a first object that include attributes to which time information is irrelevant to data processing activities and the second maps the characteristic to a second object that includes attributes to which time information is relevant to data processing activities. The second data storage schema includes a fact table including at least some facts drawn from the first data storage schema and a second dimension table that includes at least some characteristics drawn from at least one of the first object and the second object.

Abstract: A method for estimating a runtime of a query of a data repository may abstract, extract, or otherwise generate one or more parameters of the query. Thereafter, the abstracted parameters may be associated with one or more statistical query records. From these statistical query records, a query runtime may be estimated.

Abstract: A method for estimating a runtime of a query of a data repository may abstract, extract, or otherwise generate one or more parameters of the query. Thereafter, the abstracted parameters may be associated with one or more statistical query records. From these statistical query records, a query runtime may be estimated. Related apparatuses, computer program products, and computer systems are also described.

Abstract: Methods and apparatus, including computer systems and program products, relating to an information management system and aggregating data by performing table scans. In general, in one aspect, the technique includes receiving a query for a response to a search on a database, loading data from the database into memory, filtering the data based on the query to generate a list of results, buffering at least one key figure corresponding to a result, buffering at least one dimension value corresponding to each key figure, aggregating the dimension values to generate an aggregate key, aggregating key figures corresponding to the sane aggregate key to generate one or more aggregate key figures, and displaying the response to the search on a display device. Loading the data may include compressing the data. Filtering the data may be performed blockwise.