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Josh Herritz
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Nice work by +Noah Willman.
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You know that data lake you recently started filling? Its data ecosystem is already well on its way to a catastrophic tipping point. 

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You know that data lake you recently started filling? Its data ecosystem is already well on its way to a catastrophic tipping point. 

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You know that data lake you recently started filling? Its data ecosystem is already well on its way to a catastrophic tipping point. 

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You know that data lake you recently started filling? Its data ecosystem is already well on its way to a catastrophic tipping point.

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Are you concerned your Data Lake has become a Data Swamp? MIOsoft can help.

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Very, very interesting.
This article does an excellent job of explaining an important idea of economics. Say there's a shortage of something that people want, such as water. There are two basic ways to allocate it: using market mechanisms, by raising the price of the scarce good, or using control mechanisms, by saying "OK, everyone gets this much, and that's it." 

You often hear it said that "markets are efficient," and that's true: market mechanisms allocate resources far more efficiently than control mechanisms. (In control mechanisms, some people get more than they want, some people get less than they want, and nobody can trade, so pretty much everyone ends up unhappy.) However, there's another side to this, which is fairly obvious if you think about it: if you try to distribute water by raising its price, then the poor have to cut down on their usage, but the rich, for whom the change in price matters less, don't. 

The reason for this is what's called the "declining marginal utility of money" -- that is, if you have a million dollars, $100 is no big deal, but if you're living paycheck-to-paycheck, the same $100 means rather a lot. 

In particular, markets are very efficient at distributing dollars and water, using the principle that how much people are willing to spend on something is a good indicator of how much they want it -- but when the dollars themselves aren't distributed uniformly, they can be very bad at distributing happiness (or to be technical, what economists call "utility") and water. 

What this means in practice is that price-based distribution systems work well in highly equal societies, but increasingly poorly in unequal societies. What this means is that in an unequal society, you're stuck with two lousy options for distributing resources, pricing and control, neither of which efficiently distribute resources. Reducing that inequality increases the efficiency of markets. (Which, as any economist will tell you, ends up making everybody richer -- inefficiencies are resources which we simply lose to stupidity)

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I bet the MPAA is having so much fun right now.

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Connected data is big data, even in French.
Qu’est ce que le Big Data ?

• Évoqué pour la première fois en 2008 par le Cabinet d’études Gartner, l’expression #BigData est devenue populaire ces deux dernières années. Le Big Data désigne le phénomène d’une véritable explosion des données informatiques ou des volumes d’informations à traiter par l’entreprise. L’avènement du Web 2.0, l’engouement mondial concernant les smartphones, tablettes ou objets connectés ont beaucoup participé au phénomène. 

• Cette science est née pour exploiter ces masses d'informations. Elle consiste à développer les technologies capables d'analyser et de donner du sens le plus rapidement possible à ces informations. Outre leur volume, celles-ci ont la particularité d'être hétérogènes : soit structurées (comme celles déjà bien ordonnées au sein de bases de donnés), soit, le plus souvent, non structurées (textes, journaux...).

• La quantité de données produites par les êtres humains double tous les 2 ans, et sera multipliée par 10 entre 2013 et 2020 selon l’International Data Corporation (IDC). 
Des données collectées sont inexploitables si elles sont collectées sans but précis, sans question à laquelle elles doivent répondre. Les objets connectés répondent à ce problème en dédiant les capteurs, leur intégration et le logiciel d’analyse à un seul but : celui de mesurer le poids pour l’appareil MyBiody Balance par exemple !

• Aujourd’hui, les fabricants d’objets connectés devront offrir un véritable service à partir de la donnée et non la restituer de manière brute : pour collecter toutes les données générées sur ces réseaux sociaux, il existe aujourd’hui des plateformes qui stockent et sont capables de représenter les données sous formes de graphiques.

Pour vous, quels sont les enjeux du Big Data ?
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This is superb.
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