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The Data Consumer

Data what?

This is the first of a series of posts dealing with societal questions of interest to us laymen in our daily life struggles: salaries, health, cost of life, energy, water, commodities but also science and technology matters. I hope to be able to post regularly, perhaps (twice a month or weekly, time permitting). To do this, I fish from available institutional data or published papers, to cherry pick among topics I find interesting (and hopefully you will too). More often than not, apparently simple questions from media or other sources, lead to answers which are complex or difficult to interpret, verify and reproduce without access to the sources (data!) and the pondering necessary to understand the methods employed to get to the results. So then, let's help the Data Consumer by explaining the tools deployed in the process. Let's the data speak in a reproducible way and help us all to become Informed Data Consumers. And when things get too intricate or controversial, I'll provide reference to the source (so you may search for your own "truth"). This service is very much in the spirit of the manifesto I first saw a while ago on KDnuggets website about the public use of data (The original open letter can be found here). A "neutral" attitude is assumed towards national or European party politics (small p's) and I am hoping to inform or clarify on useful matters of general interest (the Politics with capital P). Finally, I am not going to debunk "belly-button fluff" (rumours, scams, hoaxes or urban legends) as a ton of specialized sites exist (just try "list debunking websites" in your favourite search engine). On occasions though, I might have a shot or two (when I feel the matter really matters; or when I can't refrain to share a healthy laughter).


Contents

Roughly following my personal interests, and in random order:

  • Commodities (raw materials / minerals)

  • Energy and Water

  • Demographics

  • Climate

  • Science and technology

and maybe more.


Please note that (i) no proprietary data or reports will be posted: plenty of agencies make their revenues on similar business and (ii) the material is offered with errors and inaccuracies that are my entire responsibility (Except for the data sources of course!). Some tutorials may accompany the general discussion when I think the needs arise.

I hope you enjoy it!

Who am I?
Carlo Fanara

Following a career in IT, I spent 20+ years in physics (MSc in Nuclear Physics, Turin, Italy, and a PhD in plasma physics, Cranfield, UK).

After several years in academia, in 2008 I moved to private companies working in R&D and, since 2014 in Data Science,

My passions include Science and Languages.

I teach programming and Data Science and occasionally blog on these matters..

Current interest: Deep Learning, IoT, Time Series, and Rare Events.

Teaching
Mind your business!
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