Qualities in Data Architecture

Data architecture describes the structure of data used by a business and its applications by mapping the data artifacts to data qualities, applications, locations etc.

Pont_du_gard2000 years ago the roman writer, architect and engineer Marcus Vitruvius Pollio wrote that a structure must exhibit the three qualities of firmitas, utilitas, venustas — that is, it must be strong or durable, useful, and beautiful.

I have worked with data quality for many years and always been a bit disappointed about the lack of (at)traction that has been around data quality issues. Perhaps the lack of attraction is due to that we focus so much on strength, durability and usefulness and too little about beauty – or at least attractiveness.

But how do the three qualities apply to data quality?

  • Firmitas, strength and durability, is connected to technology and how we tend to make our data be as close to reflecting real world objects as possible in terms as uniqueness, completeness, timeliness, validity, accuracy and consistency.  
  • Utilitas, usefulness, is connected to how we use data as information in business processes. Often “fit for purpose” is stated as a goal for data quality improvement – which makes it hard when multiple purposes exist in an organization.
  • Venustas – beauty or attractiveness – is connected to the mindset of people. Often we blame poor data quality on the people putting data into the data stores and direct initiatives that way using a whip called data governance. But probably we will get more attraction from people if we make or show quality data more attractive.

SidneyOperaHouseCompared to buildings data quality are often the sewers beneath the old cathedrals and new opera houses – which also may explain the lack of attraction.

If you consider yourself a data quality professional – being a tool maker, expert, whatever – you got to get up from the sewers and make and show some attractive data in the halls of the fine buildings. You know how hard it is to make quality data – but do tell about the success stories.

GreatBeltBridge

2 thoughts on “Qualities in Data Architecture

  1. Jim Harris 22nd June 2009 / 14:34

    Henrik,

    First of all, it is great to see you sharing your data quality insights with your own blog. I am looking forward to reading your pearls of wisdom!

    I completely agree with your post. Data quality discussions are often dominated by horror stories of ugly, smelly data from the depths of the corporate information sewers.

    Too often (and I am just as guilty of this as everyone else), all the talk is about data quality failures and difficult challenges to overcome and no talk of success stories.

    It could make people believe that no one is ever successful with data quality and that there is no (data) beauty in the world.

    Our motto should be: Data Venustas!

    Best Regards…

    Jim Harris

    • Henrik Liliendahl Sørensen 21st June 2011 / 07:31

      Thanks Jim (almost 2 years belated). I have now learned always to reply to a comment on a blog 🙂

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