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Showing posts with the label big data

Is it better to prevent or correct?

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This link gives you access to all the articles and archives for </Hello CDO> “Prevention or Correction” is something society has wrestled with for a very long time. This article focuses on why our experience of “prevention or correction” ideas frames the CDO’s responsibilities and explores a linkage to a company’s approach to data. Almost irrespective of where you reside, we live with police, penal, and political systems that cannot fully agree on preventing or correcting. It is not that we disagree with the “why”; is it the “how” that divides us! I am a child of an age when lefthandedness was still seen as something to correct, so we have made some progress. A fundamental issue is that prevention is the best thinking; but if you prevent it, it does not occur. We are then left with the dilemma, “did you prevent it, or was it not going to occur anyway?” The finance team now ask, “Have we wasted resources on something that would not have happened?” When something we don’t lik

The diminishing value of a data set

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Source :  worth observing that this Dilbert was 1993 !!!!  Radar and sonar are incredible inventions as they allow us to perceive what cannot be actually seen with the naked eye.  As technology has advance and big data analysis has emerged we have gone from a simple echo to high-quality resolution.  However, the peak value for Radar is that it informs you something is there which requires low resolution and very little data.  As Radar resolution has improved we can get direction and speed which requires a little more time. This new information definitely adds value to any required reactive decision. The identification of what the actual object is through increased resolution has an incremental value but not as much as knowing it is there and what direction at what speed but such information can lead to a better decision but suddenly there is an economics of cost compared to the incremental improvement in outcome.  Knowing what type of bird by species or what plane by manufacturer, doe

When Complex multi-dimensional data creates users that cannot exist

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It is all about averages.  If you have a single dimension data set, say height, with a large data set, it is probable that one user will be the average of the entire set. In a two-dimensional data set, height and weight, it is probable that one user may have these two characters as the average of the entire set. In a three-dimensional data set, inside leg measurement, height and weight, it is tending toward impossible that one user may have the three average characters of the entire set. More data makes it more probable, but also more characteristics make average persons more improbable, as mean, mode or medium. Facial recognition uses about 80 nodal points, it is (im)possible that a single data subject in large data set will be average on all points.    The point is that we think more data will create a better understanding of our users. This is unlikely to be the case. What we need to determine are the boundary conditions where the data we have access to enables better decisions.  

Data is Data. It is not Oil or Gold or Labour or anything else!

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This is also published on LinkedIn and Medium as well  Data is Data.  It is not Oil or Gold or Labour or anything else! Words, in general, are a creative symbolic linguistic invention through which people invoke concepts and meanings that are flexible enough to enable we Homo sapiens to shortcut detailed explanations.  A dog = mammal, furry, four legs, barks, teeth etc. However, words; because they are a shortcut, often lack context and relationship that add “meaning”. Words are “data” which requires the addition of meaning derived from context to “inform” the listener - to become “inform-ation.”   Love, for example, can mean, or be interpreted to mean, many propositions depending on context and relationship. The 2019 update to the New Oxford Dictionary brings in the words   agender and intersexual to help define better and enable more nuanced conversations about  sexuality and gender identity, as society has words without the specific context and better words help avoid

So you think you know why you do things ? Does your digital footprint reveal something we don't want to face up to?

We humans set a premium on our own free will and independence ... and yet there's a shadowy influence we might not be considering. As science writer Ed Yong explains in this fascinating, hilarious and disturbing talk, parasites have perfected the art of manipulation to an incredible degree. So are they influencing us? It's more than likely. Love the challenge and what data might tell us that we don't want to know. 

Legal aspects of digital data, thinking about data ownership

Alexander Duisberg Partner @ Bird Bird, talks to the legal aspects of exploiting big data and lists his top tips for private and   public sector. He talks to : data ownership as a concept [ personally I am not sure anyone can own data, however there are rights and responsibilities] and no jurisdiction has a fully developed concept of data ownership to date. privacy aspect of data  understanding what data you own and how it affects your customers’ privacy. licensing implications when buying or selling data and the issues of making data anonymous. 

My Digital Footprint - Data, Sorted, Arranged and Presented. Demo using lego!

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Big Data Value initiative from the EU - asking for input on focus

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Share your views - Public Consultation on the Big Data Value Strategic Research and Innovation Agenda now open! The European Technology Platform for Software and Services NESSI, together with partners from the FP7 project Big, have drafted a Strategic Research and Innovation Agenda (SRIA) on Big Data Value. The objective of the SRIA is to describe the main research challenges and needs for advancing Big Data Value in Europe in the next 5 to 10 years. The SRIA will be an important channel for providing input to the European Big Data Value Partnership that aims to establish a Public Private Partnership on Big Data Value. The goal of the Big Data Value contractual Public Private partnership (cPPP) is to increase the amount of productive European economic activities and the number of European jobs that depend on the availability of high quality data assets and the technologies needed to derive value from them. This survey is open to all and will be accessible until 5 May