Clouds and Sunk IT costs: Cloud vendors should swap their sales force for their accounting ops team

Accountant

“In the last few weeks, I have heard from several organizations, they are getting less and less concerned about cloud security, availability etc. But they are scared to go to the CFO and say let’s write off that sunk cost of infrastructure or the unamortized ERP project cost.”

“Cloud vendors cannot pretend the issue does not exist. Best if they model for each prospect the impact of the writeoff versus the savings they could be getting from the cloud and play that back as part of the sales process.”

via deal architect : Cloud Competition: Sunk IT costs.

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5 Best Data Visualization Projects of the Year – 2009 | FlowingData

With all the new projects this year, it was hard to filter down to the best, but here they are: two honorable mentions and the five best data visualization projects of 2009. Visualizations were chosen based on analysis, aesthetics, and most importantly, how well they told their story (or how well they let you tell yours).

via 5 Best Data Visualization Projects of the Year – 2009 | FlowingData.

Darwin

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Great Visualisations: The top 250 best movies of all time Map

The top 250 best movies of all time Map | Vodkaster – Le Blog de la cinéphilie 2.0.

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Answers to questions I’ve asked myself: Where is the best place to go during a zombie attack?

I09 has linked to an article in Live Science which links to a physics paper in  Physics Rev E which states that random walk annihilators (which can be thought of as the zombie class) are less effective in complex structures.

The results show that the asymptotic survival probability is site-independent of recurrent structures (d-tilde <=2), while on transient structures (d-tilde >2) it can strongly depend on the target position, and such dependence is explicitly calculated.

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Answers to questions I’ve asked myself: Could humanity survive a zombie attack?

Shaun of the Dead

Working with a professor and two other graduate students, Munz built a mathematical model of a city of one million residents, in which an outbreak occurs when a single zombie arrives in town. He based the speed of zombie infection on the general rules you see in George Romero movies: after getting bitten, people turn into zombies in 24 hours…

When he ran the model on a computer, the results were bleak. “After 7 to 10 days, everyone was dead or undead,” he says. He tried several counterattacks. Quarantining the zombies didn’t work; it only bought a few extra days of survival for humanity. Even creating a “cure” for zombification led to a grim result. It was possible to save 10 to 15 percent of the population, but everyone else was a zombie. (The cure in his model wasn’t permanent; the cured could be rebitten and rezombified.)

But it’s not all bad news, at least for those who are not early victims in the attack:

There was only one winning solution: fighting back quickly and fiercely. If, after the first zombies emerge, humanity begins a policy of “eradication,” then the zombies can be beaten.

Of course, if this solution is taken seriously by policy makers, anyone stricken in the early days of the next killer epidemic might construe this news as bad.

via The Ninth Annual Year in Ideas – Magazine – NYTimes.com.

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I like their attitude!

If you manufactured hardware, wouldn’t you want a bunch of these guys around?

“One of the benefits of not having a huge staff and a huge VC investment is that we don’t have to have unrealistic goals for unit sales,” Spence continued.

There will be lots of support for those who want to hack the device. Any needed third-party programs or drivers needed will be made available as soon as possible.

“I am very interested to see what hackers do,” said Spence. “Because of the numbers involved, if you have 10 guys and gals that start going crazy over these things, that’s probably going to take us to capacity for the first drop.”

via A New, Now Netbook You Can Actually Buy: PsiXpda.

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Climategate and Tiger Woods

Everyone who likes data has been enjoying Climategate. It is to stats geeks what Tiger Woods is to golf fans: a welcome drink of scandal in a dry desert.

Nevertheless, in Climategate, as in the Tiger Woods scandal, there’s lots of people being dragged through the mud who probably don’t deserve it. Phil Jones, the author of the charting “trick” email, falls into this category. In 1999, Phil drafted an email in which he describes increasing the length of a data series to “hide the decline” in temperatures over recent years. Admittedly Phil didn’t chose his words wisely, nor did he fully examine his unease at reporting the data as he did but he is not the scoundrel certain commentators have described him to be and certainly should not lose his job because of this email.

Junk Charts sums up Phil’s failings thus:

What concerns me is Phil Jones’ describing what he did as a “trick” to “hide the decline”.  He apparently thought that he was doing something shameful. But when is it shameful to extend the plot of a time series so as to display the long-term trend, and not be misled for short-term fluctuations? This is providing statistical context to the data being examined. Lots of people are condemning this as a willful act to mislead the public but if they have some statistical literacy, they will understand that finding the appropriate time scale to look at the data is one of the most important tasks of analyzing time series data. It’s a problem when even prominent scientists do not comprehend why they should be doing this.

I’m inclined to be even more lenient in my assessment of Phil. I’m sure he knows that determining time scale is a critical part of time series analysis and that doing so isn’t ‘hiding’ data. I’m also sure that Phil significantly tightens up his email drafting from now on.

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Get rid of the clutter

Here’s another fact to clutter up your brain: Google displays 895,000 search results for the phrase “Get rid of clutter”.

There is a ton of people looking to get rid of clutter. Two sites answering their call in very different ways are Indexed and Balsamiq.

Indexed

Indexed displays a simple chart each day comparing one or two measures along two dimensions:

The charts exclude all clutter (including scale) to focus on the critical aspects of the measures – the trend.

Balsamiq

Balsamiq is wireframe software used to emulate software user interfaces and workflow in pre-development user acceptance testing. It is similar to Axure and iRise minus the patent infringement law suits (again, less clutter).

mytube

Like Indexed, Balsamiq has gone for the hand-drawn look to focus the user on what’s important – the application flow rather than font or the colour.

These are great examples of removing complexity to increase functionality. With some excitement, I am awaiting the day when someone makes my ERP system look like my daughter’s doodle pad.

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Great visualisations: The Berlin Wall: 20 Years Later

The Berlin Wall: 20 Years Later – The Berlin Wall Through Time – Interactive Feature – NYTimes.com.

If the purpose of a visualisation is to enhance understanding, the above NYT article does exactly that. It shows 5 pictures of the Berlin Wall taken in 1989 and compares them to 5 photos taken this year.

This sort of before and after format is well travelled (think weight loss and plastic surgery ads) but the slider mechanism used in the NYT article is particularly effective at allowing the viewer to explore the differences.

Unsurprisingly, the authors of the article couldn’t help but spin the differences and, like the before and after ads where the model is slumping and frowning in the ‘before’ and standing straight and smiling in the ‘after’, the NYT ‘before’ pictures are taken on communist-grade black and white film whereas the ‘after’ are full colour.

Tip: Seth Grimes

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In data we trust … or do we?

We have made great strides in the past 40 years in collecting data and storing it in findable formats. The internet and Google are the standout examples of this activity.

But I reckon we’ve just about come to the end of that as a business model. We have refined the pay-per-click model about as far as we can.

foreclosure-streetIn my view, the next round of big money is going to come from identifying the level of trust we should have in our data. A good example is the Standard & Poors / Experian alliance recently announced. Both companies have massive data sets – S&P has data on mortgage backed securities and Experian has consumer credit data – and each has made a business out of providing this data to their customers. But together these data sets enable the end purchasers of mortgage-backed securities for the first time to accurately assess the underlying value of the mortgages (loans minus potential defaults).

I’ll be watching with interest the alliances that form over the next couple of years to unlock trust capital in existing data sets – and the privacy bun-fights that will inevitably erupt as these alliances take shape.

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