Data Transcendentalism

Data Transcendentalism

Jul 21, 2010 by in Data Quality, Metadata

Extending the topic of my blog post Predictably Poor Data Quality to include metadata, Beth Breidenbach wrote the excellent blog post Predictably Poor MetaData Quality, where she explained how “similar human motivations come into play for metadata quality as with data quality.”

“Human behavior,” according to Beth, “is both the root cause and the solution.  Technology doesn’t cause or solve the data quality challenge.  Rather, it’s a tool that exacerbates or aids human behavior in either direction.”

I definitely agree with Beth.  I have always found it puzzling when organizations try to resolve people issues by applying more technology or simply better technology.

Only people can resolve people issues.

I believe that a big part of the problem is the fact that the word “data” is prevalent in the names we have given industry disciplines and enterprise information initiatives. 

For example, data management, data architecture, data administration, data quality, data integration, data warehousing, and data governance—to name but a few.

Even the simplistic definition of metadata as “data about data” can make metadata management sound like a recursive reinforcement of the supremacy of data.

Data Transcendentalism

In the comments of my blog post What’s the Meta with your Data?, I coined the term Data Transcendentalism, which is a reference to the 19th century philosophical movement started by, among others, Ralph Waldo Emerson, whom I now paraphrase:

“So shall we come to look at the world of data with new eyes. 

We shall find answers to the endless inquiries of business insight.  What is a Shared Version of the Truth?  What is the importance of high quality data?  What is the purpose of data governance? 

Only your people, and not data, business process, or technology, can answer these questions.

Build, therefore, your own data management best practices. 

The faster you can avail your entire organization of the business understanding already present within your unique culture, but not yet shared across the enterprise, the sooner you will realize your organization’s great potential. 

A corresponding reliance on the human side of business will transcend data, business process, and technology, and it will be your people who will lead the way.”

My point is that although people, business process, data, and of course, technology, are all important, by far the most important of all is—People. 

Therefore, before you get too immersed in the intricate and low-level details of any of the many industry disciplines and enterprise information initiatives that start with data, I highly recommend that you first consider Data Transcendentalism.

Join the Data Transcendental Club

If you are a like-minded data professional who believes in a “people first” approach, then please “join” the Data Transcendental Club by posting a comment below.

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4 Responses to “Data Transcendentalism”

  1. Phil Simon

    Jul 21, 2010

    Great post, Jim.

    “Human behavior,” according to Beth, “is both the root cause and the solution. Technology doesn’t cause or solve the data quality challenge. Rather, it’s a tool that exacerbates or aids human behavior in either direction.”

    Very well put.

    I also have found it puzzling when organizations use technology to deal with what are fundamentally people issues. Part of me wants to blame ambitious software vendors but, let’s be honest, they can’t shoulder all of it. Organizations themselves need to shoulder a good chunk of the burden for failed technology projects. There’s no such thing as a perfect or error-proof systems. CIOs ought to know as much.

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  2. Monis Iqbal

    Jul 21, 2010

    Again very nicely written, you always take full marks on that part :)
    I think everyone would agree with the “people first” view. My question is which people in the organization? the ones who are running it? ones responsible for data? …
    I’m asking this because people change in an organization and this means if the ones managing the data are like-minded and care for data quality, when they leave the organization do they also leave their data quality vision with them? Isn’t the solution here is “process” rather than “people” in an organization?

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  3. Jim Harris

    Jul 21, 2010

    Thanks Phil and Monis for “joining” the Data Transcendental Club!
    :-)

    @Phil – Yes, in my experience, organizations tend to blame failed technology projects on the wrong technology being used. A better technology is sought, magically found, and then history slowly and expensively repeats itself. This doesn’t mean that technology is never to blame, but as you have previously noted, technology in no way obviates the need for people to continue to be involved.

    @Monis – You make an excellent point, and I agree that well developed processes are important for many reasons, including alleviating the risk associated with people leaving the organization or changing their roles within the organization. However, a process doesn’t create, maintain, or continually improve itself. People still need to be involved. Exactly who and exactly what their responsibilities are will change over time. However, I have witnessed too many organizations assume that after they have implemented a technology or a process, the people aspect of it is over–which, in my experience, only creates a disaster waiting to happen.

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