Abstract—The discovery, representation and reconstruction
of Business Networks (BN) from Network Mining (NM) raw
data is a difficult problem for enterprises. This is due to huge
amounts of e.g. complex business processes within and across
enterprise boundaries, heterogeneous technology stacks, and
fragmented data. To remain competitive, visibility into the
enterprise and partner networks on different, interrelated
abstraction levels is desirable.
We show the query and data processing capabilities of a
novel data discovery, mining and network inference system,
called Business Network System (BNS) that reconstructs the BN
- integration and business process networks - from raw data,
hidden in the enterprises’ landscapes. The paper covers both
the foundation and the key data processing characteristics
features of BNS, including its underlying technologies, its
overall system architecture, and data provenance approach.
Index Terms—Data processing, data provenance,
information retrieval, network mining.
Daniel Ritter is with the Technology Development at the SAP AG,
Walldorf, BW 69190, Germany (e-mail: daniel.ritter@sap.com).
Cite:Daniel Ritter, "Advanced Data Processing in the Business Network System," International Journal of Machine Learning and Computing vol. 3, no. 2, pp. 190-194, 2013.