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Data Quality: Driven by Function and Form or Glue and String?

Is the data quality in your enterprise driven by function and form or held together by string and glue?  How did you map and build the data structures required to support the functions of the enterprise?

Did you start with Business Functions, build a fully normalised, convergent Logical Data Model (LDM) and then base all of your systems database structures on this LDM?

If so, your data will probably have the integrity, symmetry and clarity of the picture on the right.

Or did you take a “real world” approach, look at all of your disparate system databases, see what data they held and then try, using an “agile” approach, to get an overall view of it?

If so, you probably ended up with data structures looking something like this picture of fragmented shards of pottery. But, how hard can it be to make a complete piece of pottery from these?

Its bound to be especially easy in the twenty first century with all of the amazing data quality software available in the marketplace.  In now time at all (the vendors said as much) all will be as good as new – perhaps even better.

Applying all of the power of these tools  you would be able to arrive at “fully integrated” data structures with all of the integrity of our creatively repaired plate to sustain your enterprise into the future.

Don’t get me wrong, data quality tools have their place and, when properly applied, can bring great benefits in finding and removing data errors.  However, they are of little use in preventing errors arising as the result of flawed analysis and data structures.

Data Quality Equation

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