xpert BI


Extract 10x faster with automated routines into user friendly data models for the entire BI solution.

idealized data sources


As an implicit extract function, the original relational model is converted to a surrogate key based data model. This function contributes to the idealizing process by providing single column primary- and foreign keys to the data model. Combined with key column naming conventions, the result is an extremely readable (idealized) data model. The visual effects of idealization are materialized in Xpert BI’s operational data store.

The surrogate key based data model handles missing relationships in the model in such a way that inner joins can be used without losing data – across missing relationships. Creating surrogate keys upfront also plays a significant role in profiling and consistency check, and for master data integration and in dimensional modelling. The visual documentation level of an idealized database is such that one can understand 80 – 100% of the content and relationships without any other data source documentation and is therefore an ideal source for further transformation processes.

“Idealization” is a BI Builders term to describe an understandable and intuitive relational database produced by Xpert BI based on any available relational data source. Idealizing a data source does not imply any changes to the data or its relational structure. The necessary metadata information (tables, columns, keys, & relationships) are imported into and/or defined in Xpert BI which then structures the data model into an idealized data model.

Time-saving metadata models


In Xpert BI, the data warehouse model is designed in metadata, and you have one single metadata model where you design and make changes to your entire project. This metadata driven approach results in building the asset in 10% or less time compared to traditional methods.

Building your model with xpert bi

  • Import metadata into Xpert BI and receive suggested table names, column names and extended relationships if Application Repository exists.


  • Refine metadata relational model by exporting a complete metadata database from Xpert BI to SQL Server where keys and relationships are refined, added, removed, and changed. Then import the refined metadata model into Xpert BI.


  • Supply naming convention on tables and columns by choosing source name, suggested friendly names or enter manually column by column. It is also an option here to export the complete metadata model from our product to an Excel workbook for manual refinement. Thereafter import the metadata model from Excel into our product again.

xpert bi native metadata support

  • Xpert BI supports automatic metadata import from all systems that reside on:

    • SQL Server
    • Oracle
    • DB2 (LUW, iSeries, zOS)

    The Xpert BI metadata import, reads table names and column names from the database system and keys and relationships where this exists.
    In addition to the native metadata import, Xpert BI also has specific metadata support for certain ERP and CRM systems with the Application Adapters.

efficient data loads

Xpert BI Extraction optimizes data loads with minimum impact on the source application. Xpert BI handles parallelization of data loads dynamically and automatically so that the data is loaded as fast as possible. Incremental data loads and filter settings are done with simple configurations and all data loads are logged in the system.