Business data model

The Benefits of Implementing a Business Data Model for Data Governance

Torsten Priebe
June 8, 2023 | 6 min read
Generic modelling techniques are often used in large data warehouses (DWHs) to ensure flexibility and stability. However, such approaches are not suitable for adequately mapping the technical requirements. The harmonization of data definitions and the assignment of data governance responsibilities require a technical model in addition to the implementation-focused view.

At Accurity, we focused the development of our Business data model and data catalog solution on the business data modelling (BDM) integrated methodology that has an emphasis on design, source mapping, ETL development, and testing to data quality assessment by data stewards. Our data intelligence platform supports this procedure and thus allows an agile, professionally driven, step-by-step DWH structure.

Image 1: Business data modelling diagram

The challenge

The business intelligence (BI) landscape, especially of large multinational companies, has often grown historically and is characterized by the spread of isolated solutions. This results in inconsistent data definitions and reports. There is a lack of understanding of what data exists and where it comes from. Communication problems lead to increased development efforts and long project cycles.

Against this background, DWH initiatives are often started to force harmonization. These projects are supported, especially in the financial industry, by the demands of the regulators, which increasingly require traceability and consistency of the data reported to them. For example, the "Principles for Effective Risk Data Aggregation and Risk Reporting" (BCBS 239) explicitly require a "single version of truth", metadata, and data lineage.

Another challenge is often with a limited scope of implementation start without jeopardizing the broad usability of the DWH for the future. Experience shows a large overlap in data requirements, for example, between risk and financial management. To leverage these synergies, however, they must be recognized, and data requirements harmonized. It is, therefore, necessary to abstract from specific reporting requirements or source systems when designing a DWH solution.

Nevertheless, a clear language for communication between departments and with IT must be found. Widespread DWH modelling approaches only partially meet this requirement since they largely rely on a generic mapping of rather volatile data requirements, e.g., key figures, in order to ensure the flexibility and stability of the technical solution.

The solution

The proven approach by Accurity is an integrated business data model (BDM), which is both understandable enough to serve as a glossary for departments and formal enough to support implementation in IT.

The procedure allows the actual technical objects – customers, products, transactions, etc., to be precisely mapped and technically unmistakably defined. These objects and their properties are “packaged” into a comprehensive model that can be shared and agreed between disciplines.

The same model also serves as the basis for the IT implementation, i.e., both technical DWH and source data models are linked to it. Maintaining the references to data requirements, source, and target systems throughout ensures consistency and traceability, and ultimately, the data quality is improved.

Departments are involved throughout the life cycle, and the methodology ensures their leading role in the project. Business data modelling means that all parties involved, departments and IT, have the same understanding of the requirements. In addition, the implementation speed is improved, and the costs are reduced.

The Accurity data governance platform

The BDM process model creates a common language between departments and IT, but as with any language, some sort of dictionary is needed to facilitate everyday use. The Accurity Business data model and data catalog solution fills this gap.

Notations and tools used by business users are often not formal enough to serve as the basis for an IT implementation. On the other hand, the modelling and development tools used in IT are usually too technical and complex for specialist departments. Against this background, Simplity created the Accurity data governance platform, which is based on the business data model methodology and serves the needs of both business and IT users.

The Accurity business glossary is the platform's core. It supports the definition and management of the technical model itself and its mapping to technical data models (source systems and various layers of the DWH architecture). Department users are responsible for the harmonized data definitions, while IT is responsible for their technical mapping.

Accurity Data quality and data observability is our solution for checking data quality and the second building block of the platform. The extensive integration with the business glossary allows the definition of data quality indicators based on the technical model – the measurement is carried out, supported by the mappings in the business glossary, on the basis of any technical data model.

In addition, Accurity also offers solutions for reference data management and business data lineage.

If you would like to have a demo of the Accurity platform, you can schedule a free demo online via our website.

Torsten Priebe