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Obsessive-Compulsive Data Quality

Obsessive-Compulsive Data Quality (OCDQ) is an independent blog offering a vendor-neutral perspective on data quality and its related disciplines. I am often asked about the name of my blog. Many of my colleagues over the years would often describe me by saying “Jim is so obsessive-compulsive about data quality, but in a good way.” Therefore, when evaluating the short list of what to name my blog, it was not surprising to anyone that OCDQ Blog was what I chose.

Obsessive-Compulsive Data Quality

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Data governance is data’s best friend. Data governance will help you take good care of your data, which in turn will take good care of your business. Basically, the success of your organization comes down to a very simple question — Are you a DG person?

An old dictionary reminds us that language — and especially its everyday usage — evolves. An old dictionary also teaches us that metadata — and especially the data it defines, describes, and provides a context for — evolves as well.

While root cause analysis is important to data quality improvement, too often we can get carried away riding the ripples of what we believe to be the root cause of poor data quality.

Big data does not obviate the need for data management best practices — even though it does occasionally require adapting those best practices as well as adopting new practices.

Big Data is Just Another Brick in the Wall

What “spinach” has your organization been falsely consuming because of a data quality issue that was not immediately obvious, and which may have led to a long, and perhaps ongoing, history of data-driven decisions based on poor quality data? Popeye said “I yam what I yam!” Your organization yams what your data yams, so you had better make damn sure it’s correct.

In Doctor Who, the TARDIS, which stands for Time and Relative Dimension in Space, is the time machine and spaceship the Doctor and his companions travel in. The TARDIS is arguably the Doctor’s most important asset, but its location changes frequently, both during and across episodes. So, in MDM, we could say that Location is a time and relative dimension in space where we would currently find an Asset.

Imagine logging into your email every morning and discovering: You currently have (∞) Unread Messages. However, I’m sure most of it probably would be spam, which you obviously wouldn’t have any trouble quickly filtering (after all, infinity minus spam must be a back of the napkin calculation), allowing you to only read the truly useful messages. Right?

Debuting August 16, 2012, I host "The Open MIKE Podcast" which is a video podcast show discussing aspects of the MIKE2.0 framework, and featuring content contributed to MIKE2.0 wiki articles, blog posts, and discussion forums. To learn more about MIKE2.0, visit the website: www.openmethodolo...

Social media is often over-identified with the technology that enables it, when, in fact, we have always been social, and we have always used media, because social media is about humans communicating in the same ways they have always communicated, by sharing images, memories, stories, words, and more often nowadays, by sharing photographs, videos, and messages via social media services such as Pinterest, Vimeo, and Twitter. To learn more, watch this video:

Inspired by a Twitter conversation with Daragh O Brien, this blog post observes that big data doesn’t necessarily require more data management — we just need to exercise better data management:

Imagine if you could somehow travel back in time and prevent specific business-impacting occurrences of poor data quality from happening. You could reactively wait and see if something bad happens, and if it does, then you could travel back in time and proactively prevent just that particular bad thing from happening to your data quality. This approach is known as Retroactive Data Quality — It’s been implemented at least three times:

Retroactive Data Quality

The Data must abide both the Business and the Individual. The Data abides the Business if data proves useful to our business activities. The Data abides the Individual if data protects the privacy of our personal activities:

“Putting data quality technology to its fullest possible use is all any corporate entity can ever hope to do.” —

Recognizing the eventual need for aspects of both a top-down and a bottom-up approach with data governance can leave an organization at a loss to understand where to begin, hovering forever in mid-decision, spinning in perpetual thought, unable to land a first footfall on their data governance journey—and afraid of falling flat on the buttered side of their toast:

Data governance success requires effectively balancing bureaucracy and business agility:

Data Governance Star Wars

Like truth, beauty, and singing ability, data quality is in the eyes of the beholder, or since data quality is most commonly defined as fitness for the purpose of use, we could say that data quality is in the eyes of the user. But how do users know if data is truly fit for their purpose, or if they are simply being presented with information that is aesthetically pleasing for their purpose? —

Companies such as Google and Facebook are winning the Data Cold War because they have capitalized socialism. i.e., socialized data in order to capitalize data as a true corporate asset:

Continuous improvement enables better decisions with better data, which drives better business performance — as long as you never stop looping the Decision-Data Feedback Loop, and start accepting that there is no such thing as a root cause:

An organization’s success is measured by the quality of the results it produces. Those results are dependent on the quality of its business decisions. Those decisions rely on the quality of its information. That information is based on the quality of its data. Therefore, data must be viewed as a corporate asset because high quality data serves as a solid foundation for business success:

If data quality issues exist (and they do), then no one wants to be blamed for causing or failing to fix them. It’s as if everyone is afraid that they will be forced to wear The Scarlet DQ:

An hommage to one of my all-time favorite Walt Disney Pictures — Finding Nemo — and also to the critically important role into which data quality is cast within all of your enterprise information initiatives, including business intelligence, master data management, and data governance. I hope you always remember: “Data are friends, not food.” —

Finding Data Quality

We need to start thinking outside the data warehouse:

The Data Outhouse

This is an excerpt from "The Idea of Order at Key West", one of my favorite Wallace Stevens poems, which provides an example of how our re-imagining of reality shapes the world around us, and allows us to discover order and meaning amongst the chaos:

The Idea of Order in Data

Envelopes are just as important as the message they deliver for three reasons: (1) They tell your audience who you are, (2) They show you paid for the postage delivering your message, and (3) They are personally addressed to the center of your attention — your audience —

Effective blog posts provide Useful and Unique content that is Clear, Concise, and Consumable: