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Abstract-We propose a new graph-based framework for business intelligence called BIIIG supporting the flexible evaluation of relationships between data instances. It builds on the broad availability of interconnected objects in existing business information systems. Our approach extracts such interconnected data from multiple sources and integrates them into an integrated instance graph. To support specific analytic goals, we extract subgraphs from this integrated instance graph representing executed business activities with all their data traces and involved master data. We provide an overview of the BIIIG approach and describe its main steps. We also present initial results from an evaluation with real ERP data.

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We demonstrate BIIIG (Business Intelligence with Integrated Instance Graphs), a new system for graph-based data integration and analysis. It aims at improving business analytics compared to traditional OLAP approaches by comprehensively tracking relationships between entities and making them available for analysis. BIIIG supports a largely automatic data integration pipeline for metadata and instance data. Metadata from heterogeneous sources are integrated in a so-called Unified Metadata Graph (UMG) while instance data is combined in a single integrated instance graph (IIG). A unique feature of BIIIG is the concept of business transaction graphs, which are derived from the IIG and which reflect all steps involved in a specific business process. Queries and analysis tasks can refer to the entire instance graph or sets of business transaction graphs. In the demonstration, we perform all data integration steps and present analytic queries including pattern matching and graph-based aggregation of business measures.