single-version-of-truth-data-quality

Single Version of the Truth – What it means for data quality?

The phrase – ‘Single Version of the Truth’ is bandied about by most practitioners of master data management. It generally comes up when they are trying to explain to the customer what they aim to achieve with their efforts. Today, I’ll be trying to simplify the term and also try to analyze if it is something that you should aim for.
 
What does truth really mean in data quality?
 
Defining the term ‘truth’ has been a difficult task for philosophers all through history, and we have a number of definition for it. When we try to utilize the term in the field of data quality, it is generally used to mean clean data.
 
However, it is essential to point out that truth in data can be of two types –

  1. Fit for use
  2. Representing the real world as closely as possible

Clearly any data that is fit for use can be seen as the truth, but this fitness changes depending on the person/department using it. On the other hand, data can be very close to the real life entity it is representing but is useless if no one is able to get any information from it.
 
What this shows us is that the concept of truth itself is malleable and configurable. Let us see if this affects our search of a single version of it.
 
Is a single version possible?
 
As we have already seen, truth is not absolute when we are talking about data quality. In his book ‘Data Driven: Profiting from Your Most Important Business Asset’, Thomas Redman says, “A fiendishly attractive concept is…’a single version of the truth’…the logic is compelling…unfortunately, there is no single version of the truth. For all important data, there are…too many uses, too many viewpoints, and too much nuance for a single version to have any hope of success.”
 
While there might be a single ‘vision’ of the truth (that we can all have a glimpse at), when it comes down to working with the data, a single ‘version’ does not seem like something that will be helpful.
 
Is a single version preferable?
 
Another question that might arise is – ‘Even if a single version of truth in data quality is not practical, should it not be an ideal to strive for?’ Let us take another quote from Thomas Redman, “Getting everyone to work from a single version of the truth may be a noble goal, but it is better to call this the ‘one lie strategy’ than anything resembling truth.”
 
The fact remains that acceptable data quality is much more important that aiming for an intangible ‘truth’. Let the hallowed word be a part of the philosophers’ realm and aim at getting the best master data for our use.
 
What are your ideas on the same? Share your inputs experiences with single version warriors in the comment section below.
 
Note – If you want to read more about this, why not try these blog posts by three visionaries in the field of data quality – ‘Sharing data is key to a single version of the truth’ by Henrik Liliendahl Sørensen, ‘Tell me the Truth!’ by Charles Blyth, and ‘Beyond a “Single Version of the Truth”’ by Jim Harris. They had a good natured contest (something they called a blog-bout) centered on this and it is great to read their views on the topic.

 

Further Reading:

Blog – Data Credibility – A Critical Dimension to Data Quality

White Paper – Improve Enterprise Data Quality through Master Data Management

White Paper – Empower end-users with Master Data Management

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Vipul Aroh

Vipul Aroh

Vipul Aroh is a part of the Marketing team at Verdantis. Although relatively new to the field of master data management and data governance, he is fascinated by the topics and is becoming more passionate about them by the day. Vipul holds a Master’s in Business Administration from Sydneham Institute of Management, Mumbai.

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