The Data-Centric Revolution: Gaining Traction

15-SEPCOL01MCCOMB-edThere is a movement afoot. I’m seeing it all around me. Let me outline some of the early outposts.

Data-Centric Manifesto

We put out the manifesto on over two years ago now. I continue to be impressed with the depth of thought that the signers have put into their comments. When you read the signatory page (and I encourage you to do so now) I think you’ll be struck. A few just randomly selected give you the flavor:

This is the single most critical change that enterprise architects can advocate – it will dwarf the level of transformation seen from the creation of the Internet.                                           – Susan Bright, Johnson & Johnson

Back in “the day” when I started my career we weren’t called IT, we were called Data Processing. The harsh reality is that the application isn’t the asset and never has been. What good is the application that your organization just spent north of 300K to license without the data?   Time to get real, time to get back to basics. Time for a reboot!                                                                                                                  –  Kevin Chandos

This seems a mundane item to most leaders, but if they knew its significance, they would ask why we are already not using a data-centric approach. I would perhaps even broaden the name to a knowledge-centric approach and leverage the modern knowledge management and representation technologies that we have and are currently emerging. But the principles stand either way.                      – David Chasteen, Enterprise Ecologist

Because I’ve encountered the decades of inertia and want to be an instrument of change and evolution.                                                                                                        – Vince Marinelli, Medidata Solutions Worldwide

And I love this one for it’s simple frustration:

In my life I try to fight with silos                                                                                                                                                                                                         – Enn Õunapuu, Tallinn University of Technology

The Data Doctrine

Peter Aikin of Data Blueprints put up the Data Doctrine, perhaps a year ago (very much in the Agile Manifesto style). A few excerpts:

Data-Centric Thinking Values:

What are the principles of Data-Centric Thinking?

Leaders can increase organizational effectiveness by focusing on data as a central, shared resource (or better still) as your sole, non-depletable, non-degrading, durable strategic asset.

Data-centric thinking means practicing four data doctrine precepts.

That is, while there is value in the items on the right, we value the items on the left more.

Stable Data Structures Preceding Stable Code

Shared Data Preceding Completed Software

Reusable Data Preceding Reusable Code

Data Programs Preceding Software Projects

We are uncovering better ways of developing systems by doing it and helping others do it.

I encourage you to add you name to the list of forward thinkers who are endorsing this at

The Data Leaders Manifesto

This spring, four luminaries in the data industry (John Ladley, Danette McGilvray, Kelle O’Neal, and Tom Redman) unveiled the Leaders Data Manifesto at . This is an important step in getting to leadership, where the change can be, dare I say, manifested.

Some excerpts from their manifesto:

Our organization’s best opportunities for organic growth lie in data. But most organizations are far from being data driven. We find no examples of fundamental company-wide change, without committed leadership and the involvement of everyone at all levels of the organization. Thousands of success stories back up this claim.



I encourage you all to sign this as well, at sign the leaders data manifesto.

IBM and Data Centric Design

IBM has jumped onto the bandwagon: see data centric design . While the emphasis is on big data and IBM’s platforms, the thrust is clear. A few excerpts from this article:

To start moving toward data centric design means diving into the world of dark data, third party data, and your own data that you capture, but don’t capitalize on.

Consider this: Less than 1% of the data generated every day is mined for valuable insights.

Traditional data capture and analysis models are slowing progress.

Data centric design is a new vision for computing that places the processing where the data is stored

Early adopters of this vision are in research laboratories and universities, but increasingly, businesses are tapping into their mountains of unstructured data to help them make business decisions.

Mary Meeker

No less a force than Mary Meeker is on this now. In her 2016 report on the Internet Trends 2016 Code Conference, she proclaimed Data as a Platform to be one of the big emerging trends.

Next Big Wave = Leveraging this unlimited connectivity & storage to collect / aggregate / correlate / interpret all of this data to improve peoples lives and enable enterprises to operate more efficiently.

Data is moving from something you use outside the workstream to becoming a part of the business app itself. It’s how the new knowledge working is actually performing it’s job.

The Data Centric Revolution Planning Retreat

June 8-10 in the remote Rocky Mountain National Park, a small group of co-conspirators will be huddling for a long weekend. What we intend is to turn the good intentions expressed in these manifestos and some of these predictions, into tangible action plans. We are going to contemplate and debate the areas of highest leverage. Everything is on the table including: standards, reference architectures, open source initiatives, conferences, white papers, and books.

I’ll be reporting back on our findings in the next installment of this series.


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About Dave McComb

Dave McComb is President of Semantic Arts, Inc. a Fort Collins, Colorado based consulting firm, specializing in Enterprise Architecture and the application of Semantic Technology to Business Systems. He is the author of Semantics in Business Systems, and program chair for the annual Semantic Technology Conference.

  • Richord1

    Data centricity reminds me of those who believed the earth was the center of the universe.

    Of course, those of us who focus on data in our work become “data-centric”. But perhaps we have become data obsessed? Everything revolves around data?

    Organizations have always been people driven. Not software, not data driven. Data is a form of communications and data has no intrinsic value until a human interacts with it.

    In fact, we could say that we should be people-centric which is the fundamental challenge addressing the problems we face with data such as quality. We focus on the technical aspects of data and look for technical solutions ignoring the social side of data.

    Many data initiatives stall or fail. They ignore the social factors. Changing behaviors is paramount to managing data. No doubt data is important and should be better managed. But technologists haven’t been trained or skilled in dealing with the social factors. Software could be literally written in a vacuum (e.g. thrown over the wall). Data requires understanding of language, behaviors, politics and many other social factors. Data centricity does little to address this real fundamental challenge; “it’s a people problem”.

  • Chris Pehura

    It’s new! It’s improved!

    This data-centric direction is the new face of the “model-driven” direction almost three decades ago. The difference now is that there is no much confusion on the language and what data can actually do.

    It all boils down to what are the outcomes:

    Technical – managing the 4 Vs – velocity, variety, veracity, and volume.
    Business – 4 Ps – better planning, higher productivity, and deeper proficiency.
    Executive (cash flow) – stability, efficiency, liquidity, and profit

    Don’t be fooled by the next sexy face of what the industry has been doing for a long time now.

  • Richord1

    “Consider this: Less than 1% of the data generated every day is mined for valuable insights.”

    The remaining 99% of data is poorly designed, missing metadata, inaccessible, and of poor quality.

    Without Data Literacy we continue to create duplicate, ambiguous and meaningless data. A Data Centric approach built on this foundation of is not a solution. It assumes people understand data.

    We witnessed this with software. Just because you can program doesn’t make you a literate programmer (see Literate Programming – Donald Knuth). There is a lot of poorly written software out there. Lets not make the same mistake with data!

    Being Data Centric does not address the core problem of Data Literacy.

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