Journey through Enterprise IT Services
In Journey through Enterprise IT Services, Nadhan, HP Distinguished Technologist, explores the IT Services industry, and discusses technology trends in simplified terms.

From the Desk of Big Data – Infonomics begins at home

Hello Enterprise IT. This is Data.


What’s in a name? I used to make light of this, and not attribute much significance to my most primitive forms, such as a “name.” Then I came across the principle of Infonomics – applying economics to information – as originated by Douglas Laney, Gartner Research VP. This principle opens up the possibility of enterprises endowing me with tangible value, proper context, and treating me like they would other assets. This is great! However, I now realize it’s not just enterprises – but individuals such as yourself – who must do add value to me as well. Jessica Leber asserts this in A Stock Exchange for your Data based upon the white paper by Bernardo Huberman, Senior Fellow at HP Labs.

Differentiating Applications Transformation with a new style of IT

In her HP Discover keynote, HP CEO Meg Whitman explained a new, emerging style of IT. I kept this in mind when I walked into a session entitled: Application Transformation— the future will not be like the past (#TK12127) led byPaul Evans and Silvia Vigant. Evans characterized the changing landscape of applications for today's business from traditional Systems of Record to the disruptive Systems of Engagement. Both need to co-exist—just like the city of Frankfurt did it for me at the conference. What struck me was how well the applications transformation approach outlined in this session mapped to the new style of IT characterized by simplicity, agility, speed and cost.

Return On Information (ROI) using data that matters

Info_world.jpgWe all have encountered presentations where the presenter is sharing the same content, over and over, and not telling you anything new. People have an innate ability to recognize redundancy, and discard it as additional information that doesn’t add anything new. Similarly, we must only informationalize data that matters for the enterprise. In other words, duplication of data does not increase the volume of information —a key point highlighted by Dr. Michael Wu, Ph.D., Principal Scientist of Analytics at enterprise blog platform provider Lithium in a recent piece in TechCrunch. Wu provides multiple examples of redundant re-tweets, and video logs from multiple video cameras, to make his point.


Wu provides a simple inequality:



information <= data


So we can assume for the enterprise that all data is not information. But the pertinent data used with context can realize valuable information.


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