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Analysis

Enterprise Business Modelling Revisited
Andy Hayler By: Andy Hayler, CEO, The Information Difference
Published: 10th February 2010
Copyright The Information Difference © 2010
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Data governance is the label that is given to the attempt by an organisation to control and manage its data. It includes defining the ownership of data, monitoring its quality and protecting it, and setting in place processes to ensure that rules are actually followed. It is increasingly recognised as being a pre-requisite for a successful master data management (MDM) initiative. One important aspect of data governance is the definition of enterprise-wide rules that define key shared data, and yet, so far, technology vendors have mostly concentrated on providing database hubs for storing master data, and applying technical rules to this data. Actually getting business agreement on who owns what data, and what rules need to be applied to what data, is a tricky business, involving operating across organisational and political boundaries. There has been limited technology around to help (and indeed there are inherent limits on just how much technology can really help in this regard).

One important element of data governance is coming to a shared agreement on the structure of key organisational data and the processes that maintain data. Over the years there have been many attempts to build up enterprise-wide models of data and processes, from data dictionaries back in the 1980s through to CASE tools in the 1990s. These initiatives generally floundered because business people had difficulty engaging with the technical language and diagrams used by data modellers, and because the resulting models were stored in a place (perhaps a dictionary or repository) that was outside the core applications where changes to the data actually get made. This lack of an active link back to operational systems meant that the model quickly became out of date as the business developed and changed. Such initiatives often use technology to help document models that is not especially well suited to the job, such as static data modelling tools, or even spreadsheets and slides.

A company that hopes to revive interest in enterprise modelling is Collibra, a Belgian venture-backed start-up company. Originally a spin-off from a university, Collibra's technology (which has been granted several patents) draws on years of academic research into semantics to deliver a modern, intuitive environment that can be used to develop shared information models using natural language rather than technical data modelling. This incorporates such ideas as wikis (as used in Wikipedia) to enable models to be iteratively developed in a collaborative fashion by business people. The repository used is standards-based, using the Object Management Group's open standard SBVR (Semantics of Business Vocabulary and business Rules).

A run-time tool allows the linking of such models to applications via web services, thus enabling the possibility of keeping the model up to date. Collibra can read in existing models in standard formats, and can generate output in standards such as UML, OWL or other formats. The company has already built links to Oracle Fusion and some other integration technologies. It has some early customers, mainly in Benelux, from government and assorted industries, but is seeking to look further afield geographically.

While there are some enterprise-wide modelling projects going on today, the difficult heritage that these have will, in my view, make for a tough sell. However, the technology seems to be a natural fit as part of a broader solution. I can easily imagine partnerships with either integration vendors or MDM vendors, possibly even data quality vendors, who are increasingly under pressure to provide more than lip-service technical support to the data governance groups that are now springing up in large corporations. There are widely different levels of governance capabilities within existing tools, and so Collibra would seem a natural potential partner for platform vendors seeking to beef up their support for business modelling within their products. It will be interesting to see whether this latest attempt to revive interesting in enterprise business modelling can latch on to the current upsurge of interest in data governance, and succeed where previous attempts have languished.

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Published by: IT Analysis Communications Ltd.
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