The celebrity of data: Big data goes big time in your organization


We were once oblivious to data. It was in the background. Just noise. The “byproduct” of applications that we used every day. A nuisance that screwed up every system migration or install.

Now, we wonder, who’s seeing our data? How might they use it? We constantly check and review our Facebook privacy settings. Can our data have an impact on our business and personal relationships? Have you ever Googled yourself to see what others can find on you?

Organizations are asking the same sorts of questions and are viewing their data as a corporate asset. Corporate assets have a few things in common:

  1. Assets have value.
  2. That value is measurable.
  3. Assets require special skills to manage them.
  4. Assets support strategic initiatives.

What is your organization doing about data? Are you viewing your data as an asset? Are you treating your data as an asset? Are you ready to manage your data as an asset?

Here’s one way to evaluate your readiness. Tony Fisher, former CEO of DataFlux, wrote a book called the Data Asset. There, he outlined a data governance maturity model.

The Data Governance Maturity Model show the four different phases of data governance readiness and awareness. The phases are undisciplined, reactive, proactive and governed.

The Data Governance Maturity Model show the four different phases of data governance readiness and awareness.

The model shows that companies typically move from one area to the next as their ability to manage data effectively – across the organization – increases. To put you at ease, the book said that about 85 percent of all companies into the ‘Undisciplined’ or ‘Reactive’ stages. Data has long been an afterthought of both business and IT, and this explains the vast majority of people on the early stages of data governance maturity.

Another observation from the book was that no organization fell into one stage as a whole, but rather different pockets of the organization identified with different stages. This is encouraging, as there are opportunities to learn from other areas of the business.

The maturation process is one that includes technology, process and PEOPLE (as indicated in the model). The human factor is always the hardest part. We are inherently distrusting of data (see the NSA and Target fiascos in the previous post) and change.

I believe transparency and the open exchange of ideas are key to helping us deal with our inherent distrust. If you are looking at a report and your gut tells you it’s the wrong answer, what do you do? If you are looking at a report and you gut tells you it’s wrong, but right next to the report you can see where the data came from, the degree of the quality of the data and the calculations used…now what would you do?

How are you viewing your data? How are you treating your data? Most importantly…how are you managing your data? The days of assuming everything is fine are long gone. Data is an asset that you can use to benefit your organization. Or, it can paralyze – and even embarrass- you. The choice is yours.


About Author

Lisa Dodson

Manager, Data Management – Americas Technology Practice (SAS)

Lisa is a recognized expert in the data management, data governance and data quality space within the organization. A 14-veteran of SAS, Lisa holds a master's degree in information quality and has affiliations with many data management/governance organizations. She is a former board member and president for the International Association for Information and Data Quality (IAIDQ) and an organizing committee member for MITIQ's Industry Symposium. Lisa has experience as a systems engineer, product manager, technical trainer and solutions architect at SAS, where she’s developed a deep understanding of the SAS software architecture. In her current role she leads the Americas Data Management Practice.


  1. Really good points, Lisa. What factors help people develop trust in the analytics they see? Some research shows a majority of decision makers reject data that conflicts with their gut instinct. This is a complex issue and difficult to measure. But you touch on something that's central to the research I do, when you ask if seeing the data source, an indication of data quality, and the calculations used will increase likelihood that someone will act on a report that conflicts with what their gut says. And you're right, governance plays a role in this. I'd be interested in seeing research by SAS on this topic.

  2. A good perspective on an important "byproduct"...

    Another question to ask is how are you securing your data and metadata? What measures do you have in place to ensure only those that should see it, can?

  3. Taylor Armerding on

    Good post - obviously it's important to remember that data is raw material that doesn't necessarily have value just because it's collected. It needs to be structured, organized and analyzed by those with the expertise to do it. Then it can provide enormous benefit to organizations.

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