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The Joy of Data Modelling.

,

You may think that the task of teasing out the exact nature

of the data and processes within a company is a boring job. Not a bit of it! It

is half way between archaeology and forensic science, and I have spent some of

the happiest years of my life doing it, mainly as a Data Architect. I’ve done

small businesses all the way up to government departments and  multi-nationals. 

Is the job necessary? I disagree with Yourdon when he says

that the detailed understanding of the current systems in place within an

organization is unnecessary.  Having been reared on SSADM, and used various

other methodologies, I’ve experienced cases where a detailed understanding of

the current systems has saved an IT initiative from oblivion.  Often, the model

that you bring into life is the first time that the senior management of an

organization has possessed a ‘helicopter –height’ panorama of the flow and

transformation of data through the organization.  Often, if you take care over

the presentation of the model, and communicate it well, it sparks all sorts of

ideas to improve the way that the organization works; ideas that often don’t

require technology to implement.

The first thing about establishing what really goes on in a

company is that

  • No one person or group in the organization understands the whole

    general picture.

  • If you’ve got it right, then two data architects working

    independently will produce a very similar model. They’re uncovering something

    real.

  • Some people who you interview will deliberately try to  mislead

    you

  • A few people on the organization are so deluded as to hold

    entirely erratic views on what is actually going on in a company.

  • The senior management generally have only a limited grasp of what

    is going on in an organization. (I’ve known one or two remarkable exceptions to

    this)

  • The biggest struggle is to understand the broad overview. The

    greatest mistakes; the ones that cause enormous IT initiatives to fail, come 

    directly from failing to get an accurate consensus of what a company is actually

    doing before you start your initiative.

Why bother with the long-drawn-out business of getting the

data and process architecture of an enterprise right?  Often, the data

architects are seen as pedantic, doddery old veterans put safely out to grass

where they can do no harm. When companies look for cuts in IT expenditure, the

Data Architect is usually seen as an easy low-flying turkey to pick off. Nothing

stops working when they are given the mantelpiece clock. Likewise, nothing bad

happens for a while after you leap off the top of a tall cliff.  Data Architects

are important. The reasons why include

  • If companies can maintain an overall understanding of their data

    and processes, then ‘Silo-ization’ is prevented. (Silo-ization’ refers to the IT

    syndrome of having several apparently effective applications that cannot

    inter-communicate because  the data models of each application have entirely

    different assumptions)

  • The data model, if properly drawn out and presented, actually

    helps the organization to understand what it is doing well-enough to take more

    intelligent decisions and understand the pressure-points.

  • With a good corporate data model, fraudulent financial practices

    are easier to detect

  • When IT projects are started, the vital stages of business and

    system analysis can kick off much faster as the preliminary work will already be

    done.

  • Staff training and induction is much easier and less costly once

    you have a well-written and tested data model, because the data and process

    model is couched in business terms that are familiar to the staff of the

    company, and years of knowledge can be gleaned in a short time from the model.

  • Data ‘warehousing’ in all its many brands and flavors becomes much

    easier because there is a general agreement on the constitution of every

    business object.  I once worked for a bank where everyone knew what a customer

    was,  but it was only apparent that here was no common consensus  when time came

    to report on the output from two different IT projects.

Maintaining a data

model is surely the most important function an IT department can perform. In

any place I’ve worked that has managed the job of maintaining such a thing, life

for everyone has seemed, somehow magically, more simple and the reason for this

hasn’t always been obvious. In fact, whenever I’ve poured through reports of why

IT projects have failed, it has always struck me that nobody has mentioned ‘lack

of an enterprise-wide data model’, as a good reason for failure. Maybe the task

and its end-results just seem so esoteric that it is difficult to see the

connection between that and all those little C#/LINQ projects all over the

place.  Maybe, as well, people have been asking the wrong question. It should be

‘Why do IT projects succeed?’. I’m sure ‘Having a good enterprise-wide view of

your data systems’ must be up there.

(p.s. Two years ago, I expanded on this theme, in a rather more humorous vein, in  The Data Dialog over on Simple Talk)

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