The Future of Data – An Ultra Brief Summary

I wrote a lengthy report on the future of data… due to several reasons I never got around to publishing it  (yet — I’d like to eventually, but now needs some updating).

I would like to share some excerpts from this report – such as the one below.  Please let me know your thoughts and it might encourage me to publish it (might, might, might… might).

Data has been touted over the years as many things: the blood the corporation, the main asset, the most valuable part of IT’s responsibilities – and lately as “Big Data”: a vast collection consisting of real-time data that comes from all walks of life and technology.

Regardless of how it is viewed, labeled, or categorized data remains the most important component of organizations finding and defining value for interactions between stakeholders and customers.

There are, however, two aspects that merit notice and make this very different from any other time: analytics and experiences.

The Value of Analytics

Without any processing, analysis and understanding of the hidden value inherent to data it actually is nothing more than a collection of one-and-zeroes in a storage device (or transport, if it must be interpreted life from the network as opposed to picked up from storage).  The purpose of data is to be combined with other elements, mixed-and-mashed in myriad ways, and its secrets unhidden.

This is actually one the most valuable advances of the recent years: the speed of processing, the understanding of the data, the advances in storage and management, and the better knowledge of how to manage data yielded amazing advances in real-time analytics and the use of predictive analytics (or, better yet – anticipatory analytics).

Now all we need are the tools to use it properly.

This is where most of the analytics vendors that get it are working on: data visualization, data-prep, data-scrubbing and more of those tools are losing their IT-centric, consultant-deployed models and embracing the rise of the citizen programmer.  Indeed, letting the stakeholders and the users directly access the data they need to conduct analytics and manipulate the data via graphical driven interfaces is removing the need for the “data scientist” and letting more and more organizations use their data better.

This is translating into better insights, better results, and better processes being deployed in organizations – and all this is the tip-of-the-spear for the digital transformation investments that will explode in the next few years.

All They Want is Experiences

The era of the customer is upon us.  Customers are more empowered and better prepared now that at any other time in history.  Armed with online communities, other customer’s reviews, and access to infinity resources via the internet they are smarter, better educated, and more knowledgeable than organizations.  As a result, they are calling the shots in the interactions between organizations and them: deciding when and where they interact, and (more importantly) what they want to get form the interaction.

This last point is critical: most organizations are not prepared to deliver those outcomes (in the form of experiences) because they don’t have access to the right information.

Information management I shaping up to be the critical investment priority for organization in the next decade and the three elements that make up information (data, knowledge, and content) are shaping up to get generous budgets allocated to them.

Of course, it is not simply about having the right information, or knowing where to find it, but also of making sure the right data is matched with the proper content and complemented with the necessary knowledge to provide a complete, personalized, and optimized answer to the customer’s question or inquiry.

The understanding of how information is created (how data is analyzed, knowledge generated, and content maintained at the very least) is what is going to be driving infrastructure investments for IT in the next 2-3 years (and longer) as they adjust to the new reality of having to manage information using technology.

What do you think? Am I way off?

4 Replies to “The Future of Data – An Ultra Brief Summary”

  1. I felt compelled to weigh in on the “three elements on information”. As listed, data, knowledge and content may be a bit vague. While I understand that “Data” means “unstructured” collections of information and “Content” refers to that data which is much more structured and organized, I believe there is a more accurate definition of the three elements.

    I propose “Data, Knowledge and Subject” as the three primary elements. While some data may be structured and some unstructured, I feel that without a subject to measure and analyze against, the structure becomes less important.


    1. how would you differentiate subject and context further?

      this is one of the problems with definitions – starting down the path ends up in rabbit holes 🙂

      data, knowledge, and content are all structured elements in my world — if its unstructured is neither data nor very useful until it is structured from where i sit.

      I wrote recently about it, check out the post — about half-way down…

      Thanks for the comment,


  2. Whilst I do love data, I do also think that people right now are confused about its benefits and uses in a similar way that social media is also misunderstood right now too. My marketing background has basically forced me to adopt and learn about uses of data in order to make my findings and future campaigns work, but most people just seem to love the use of vanity metrics and assume that this is the way you work with it!


    1. ah, vanity metrics… my old nemesis.

      I shared some 3 years ago a post i thought was wonderful at discussing this topic:

      worth the time to find out why CSAT, NPS, friends, and some many other vanity metrics are worthless to the business – albeit fun to collect and watch grow!

      if everyone who thought they understood data would actually understand data we would live in a very different world. as it stands, and by my anecdotal research, we are about 8:1 ratio of not knowing /understanding data to understanding data. not a good place to be…


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