Sap Se

Sap Ag

Patrick Winkler

Klaus Nagel

Marcus Hoepfner

Oliver Rebholz

Matthias Jensen

Achim Seubert

Jascha Kanngiesser

Silvia Bratz

Dirk Janning

Rainer Schaefer

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.

Enterprise data warehouse model federation

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.

Systems and methods for performing data analysis for model proposals

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.

Embedded data marts for central data warehouse

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.

Secure transfer of business data to a hosted system

Growing community of inventors

Heidelberg, Germany

Patrick Winkler