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IMM world audience spans 5,ooo towns and cities in 181 countries.

IMM Audience Now in 5,000 Towns & Cities in 181 Countries

IMM the Integrated Modeling Method can truly be said to be global with an audience in nearly every country in the world, as shown by the map below from our website Google analytics. You can help us to grow our audience still further by: Sharing this page with colleagues and friends by clicking on one […]

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Business and data definitions give direction to an enterprise.

160 Pragmatic, High Quality Definitions for Business and Data Analysts

Quality Practice Begins with Quality Definitions Sadly, in the worlds of business and data analysis and modeling good definitions are hard to find, bad definitions abound and misunderstanding and misuse of even the most fundamental terms is commonplace. I am a perfectionist. I am passionate about quality and want to deliver it to my clients […]

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What’s the Matter with ‘Meta’?

Misuse is the matter with ‘Meta’. ‘Meta Data’ is a term that is beginning to appear and be misused in blogs and articles on Data Quality. Although Meta Data does have a role to play in Data Quality, it is not the one described in some Data Quality articles. In this post I will define […]

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Enterprise Architecture or Business Architecture?

On on-going discussion in Linkedin and other forums (or should that be ‘fora’?) is the difference between ‘Enterprise Architecture’ and ‘Business Architecture’. In a rational world they would both be seen as the same thing.  However, not all people who get involved in the ‘architecture’ worlds are rational! Words Matter The reason this discussion arises […]

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Address Universal Modelling Tool

Address Modelling Magic The different structures of addresses in different countries and different languages can seem to be an insurmountable obstacle when trying to bring consistency of address structures for the purposes of Data Quality and Master Data Management. Without the right tool it is insurmountable.  However, with the right tool is becomes relatively simple. […]

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The Phantom Entities of Customer and Supplier

It is amazing how much is spoken and written about Customer and Supplier, especially as they do not exist – they are Phantom Entities! Read more at There’s No Such Thing as Customer.

Recently, in a response to a comment on The Pathology of Business & Data Modelling I was addressing this topic once again and thought it would be useful to produce some models that show how Customer and Supplier are in fact Roles played by the entity Party.

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If I Wanted to Get to Dublin I Wouldn’t Start from Here: Part 1

It seems that most Master Data Management (MDM) projects are starting in the wrong place and heading in the wrong direction! They fail to build and use that essential and most powerful of MDM tools, the Logical Data Model (LDM).

This approach is about as productive and effective as building a ship without a keel!

This is the first of three posts that explain what the problems are and how top avoid them.

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Data Quality – One Version of the Truth?

The concept of “one version of the truth” is possibly the most widely discussed (and disputed) topics in Data Quality. Some say that it can never exist, others, that it must always exist or there is no quality. There is one version of the truth but, perhaps, not the truth as you know it! Know the Unique Identifier (UID) and the truth becomes blindingly obvious!

Click on “Read More” to see how.

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There Are No Such Things as Data Rules!

This may come as a surprise to many involved in Data Quality but, wait for it, there are no such things as data rules! By looking at data you can never deduce or define a rule that dictates that one entity should be related to another or that a value of an attribute of an entity has to be, in a certain format and have limits to its value. So what does dictate data content, structure, format and constraints?
Click on “Read More” and find out why….

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There's No Such Thing as a Customer!

“Customer” is one of the Data Enitities that lies at the heart of most MDM practices in enterprises around the world and it is not in fact a Data Entity at all! This situation has arisen because far too much “data quality” work is done without the use of a properly structured Logical Data Model. This work then serves to perpetuate rather than remove fragmented data structures.

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