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Adults struggle to solve puzzle kids solve with ease

February 5, 2016 By editor

A National Geographic puzzle (described below) that 80% of children can solve flummoxes most adults.

As we get older we develop a whole range of skills that allow us to operate more efficiently. The problem is that these optimizations result in blind spots and lowering of creativity.

Now, don’t get me wrong—the tradeoff is worthwhile. You really don’t want a six-year-old in charge of your data analysis strategy. Creativity is over emphasised in modern business writing. However, clearly we should try to eliminate some our harmless biases.

This is where decision and data science help. Mathematical models, formal decision making processes and real-world data can challenge our preconceptions. When confronted with a gut-feeling square peg that won’t go into the round hole of a formal model we are forced to confront our biases and re-frame our understanding of our environment.

Alternatively, we can angrily toss out the model and data for disagreeing with our cherished theories—but that’s politics for you.

The puzzle

The puzzle is to work out which way the bus shown at the top of the post is traveling.

Filed Under: Decision science Tagged With: bias, creativity

Microsoft speeding up tonight’s Iowa caucus

February 1, 2016 By editor

Microsoft is providing technology for tonight’s Iowa caucus that should

facilitate [the] accuracy and efficiency of the reporting process

It also gives the company, which is seeing strong grow in its cloud services, to showcase its cloud and mobile offerings in a high stakes setting.

Filed Under: Big data Tagged With: cloud, Microsoft, politics

Doug Cutting on the future of Hadoop

February 1, 2016 By editor

Data Informed have published interview with Doug Cutting on the future of Hadoop.

He makes a number of observations.

On MapReduce…

MapReduce is on its way to being legacy.

On important Hadoop developments…

I think Kudu is very exciting; a new storage engine that offers a lot of low-latency, random-access capabilities that HDFS doesn’t while still permitting the fast analytics that you can do on the flat files in HDFS.

On deployment…

…providing a vendor-neutral cloud, so you don’t have to be locked into an Amazon or a Microsoft or a Google but retaining the option to move your data and operations, we think is important.

On hardware developments…

it’s pretty clear what the next hot hardware area is: memory technologies that are coming out that give you orders of magnitude faster access to persistent storage and also, combined with that, hardware that lets you access that memory over a network without involving the remote CPU, so basically every machine on a cluster can have micro-second-level access to all the memory in that cluster. And that’s going to be a game changer.

Filed Under: Big data Tagged With: Hadoop

Worst passwords of 2015

January 30, 2016 By editor

SplashData, a purveyor of password managers, has produced its annual list of the year’s worst passwords.

The top ten are

  1. 123456
  2. password
  3. 12345
  4. 12345678
  5. qwerty
  6. 123456789
  7. 1234
  8. baseball
  9. dragon
  10. football

I guess we should all be shocked at how poor these passwords are. However, there’s no breakdown of which sites these passwords came from.

If they are all from bank accounts then, yes—OMG! However, if the bulk of them are from “sign up to read this article” sites then, meh. If I create an account just to download a free PDF, I don’t care in the slightest if my account is hacked.

To draw conclusions about behavior we need to play close attention to context.

Filed Under: Behavioral economics, Data science

Don’t trust the polls

January 28, 2016 By editor

2016 is the year of the US presidential election. Prepare to be besieged by polls. The embarrassment of the 2015 UK parliamentary election predictions is a distant memory. We get to start over.

However, Mona Chalabi reminds us, via the Guardian’s Datablog, of the challenges facing pollsters. She lists five:

  • The media are fallible. They follow fashion and make the news.
  • Journalists are fallible. They are biased—just like the rest of us.
  • Predicting the future is hard. Context shifts.
  • It’s difficult to reach people. There’s no longer a household landline.
  • People don’t want to be polled. The few who do probably have something in common.

That’s a pretty damning list—and it’s far from exhaustive.

Of course, if we don’t have poll results we’ll have to have news stories about the issues…and who’s got time for that?

Filed Under: Data science Tagged With: polling

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