Interesting Quotes

Statistically, strength comes from pooling people together, but then the icing on the cake is when you individualize the findings.
— Patrick Wolfe, a statistician who studies social networks at University College, London.

Recent Read: big data and personal analytics

The Data Made Me Do It

The next frontier for big data is the individual

 

http://www.technologyreview.com/news/514346/the-data-made-me-do-it/

 

Would you trade your personal data for a peek into the future? Andreas Weigend did.
The former chief scientist of Amazon.com, now directing Stanford University’s Social Data Lab, told me a story about awakening at dawn to catch a flight from Shanghai. That’s when an app he’d begun using, Google Now, told him his flight was delayed.
The software scours a person’s Gmail and calendar, as well as databases like maps and flight schedules. It had spotted the glitch in his travel plans and sent the warning that he shouldn’t rush. When Weigend finally boarded, everyone else on the plane had been waiting for hours for a spare part to arrive.
For Weigend, a fast-talking consultant and lecturer on consumer behavior, such episodes demonstrate “the power of a society based on 10 times as much data.” If the last century was marked by the ability to observe the interactions of physical matter—think of technologies like x-ray and radar—this century, he says, is going to be defined by the ability to observe people through the data they share.
So-called anticipatory systems such as Google Now represent one example of what could result. We’re already seeing the transformations that big data is causing in advertising and other situations where millions of people’s activity can be measured at a time. Now data science is looking at how it can help individuals. Timely updates on a United Airways flight may be among the tamer applications. Think instead of statistical models that tell you what job to take, or alert you even before you feel ill that you may have the flu.

Recent Read: Experiments: What happened when one man pinged the entire internet

http://www.technologyreview.com/news/514066/what-happened-when-one-man-pinged-the-whole-internet/

A home science experiment that probed billions of Internet devices reveals that thousands of industrial and business systems offer remote access to anyone.

A  Map of all systems that were online and were pinged!

You probably haven’t heard of HD Moore, but up to a few weeks ago every Internet device in the world, perhaps including some in your own home, was contacted roughly three times a day by a stack of computers that sit overheating his spare room. “I have a lot of cooling equipment to make sure my house doesn’t catch on fire,” says Moore, who leads research at computer security company Rapid7. In February last year he decided to carry out a personal census of every device on the Internet as a hobby. “This is not my day job; it’s what I do for fun,” he says.

Recent Read: Internet of things

http://venturebeat.com/2013/04/29/internet-of-things-ibm/

While we’re still figuring out what the Internet of Things will eventually look like, we do know this: It’s going to be very, very busy.

To help make sense of the noise IBM is announcing MessageSight, a new, somewhat mysterious appliance that will help manage the flood of data coming from Internet-connected sensors and devices. To pitch the need for the box, IBM cites data from IMS Research, which says that there will be 22 million web-connected devices by 2020. All these devices, which will generate 2.5 quintillion bytes of data per day, are going to need hardware to process them — or so IBM says.

If the understanding of the “Internet of Things” still eludes you, envision a scenario where every component of you car had its own sensor, and all of these sensors periodically phoned home about what was going on inside them. Leaky tire? Faulty brake light? Empty fuel tank? With sensors, your car could keep track of this information and warn you when bad Things are going down. But getting sensors in devices is easy. The real challenge is processing all of their data.

Recent Read: Data visualization

http://hbr.org/special-collections/insight/visualizing-data
http://blogs.hbr.org/cs/2013/04/tell_better_data_stories_with.html

 

Tell Better Data Stories with Motion and Interactivity

When it comes to making sense of vast amounts of complicated data, time really is on your side. It's a simple concept, one that everyone understands: an action starts, then eventually stops. The distance between those two points conveys information — information about then, about now, and about the differences between the two.

If you apply that simple yet elegant measuring stick to an overwhelming glut of information, you have the beginnings of a powerful data visualization that can simplify the complex, identify trends, and shape your audience's comprehension of the story you want to tell.

However, when time is the canvas for your data, you'll need one, or both, of these techniques: motion and interactivity.

Hans Rosling, who gained popular fame in his 2006 TED Talk on "stats that reshape your worldview" uses the power of motion in the software that runs his Gapminder trend-finding operation.

 

http://blogs.hbr.org/cs/2013/03/when_data_visualization_works--and.html

 

When Data Visualization Works — And When It Doesn't

I am uncomfortable with the growing emphasis on big data and its stylist, visualization. Don't get me wrong — I love info graphic representations of large data sets. The value of representing information concisely and effectively dates back to Florence Nightingale, when she developed a new type of pie chart to clearly show that more soldiers were dying from preventable illnesses than from their wounds. On the other hand, I see beautiful exercises in special effects that show off statistical and technical skills, but do not clearly serve an informing purpose. That's what makes me squirm.

Ultimately, data visualization is about communicating an idea that will drive action. Understanding the criteria for information to provide valuable insights and the reasoning behind constructing data visualizations will help you do that with efficiency and impact.

For information to provide valuable insights, it must be interpretable, relevant, and novel. With so much unstructured data today, it is critical that the data being analyzed generate interpretable information. Collecting lots of data without the associated metadata — such as what is it, where was it collected, when, how and by whom — reduces the opportunity to play with, interpret, and gain insights from the data. It must also be relevant to the persons who are looking to gain insights, and to the purpose for which the information is being examined. Finally, it must be original, or shed new light on an area. If the information fails any one of these criteria, then no visualization can make it valuable. That means that only a tiny slice of the data we can bring to life visually will actually be worth the effort.

utilities: How to mail merge

http://help.thunderbird.edu/content/how-do-i-mail-merge

How Robots and Military-Grade Algorithms Make Same-Day Delivery Possible

http://www.wired.com/business/2013/03/online-retailers-faster-than-overnight/

more comments to follow:

Key themes:

• Store to door
• Predictive stocking
• 7-11 lockers
• Man+ machine integration in picking right items and humans figuring out quality
• City as a warehouse (how ebay has participants from Walgreens to radioshack to THD)
• Couriers (with mobile app tracking)

Forget next-day delivery. The standard in online shopping is rapidly approaching next-hour delivery. Retail giants Walmart, Amazon, and eBay, and a few nimble startups, are testing same-day services, bringing whatever you desire—ice cream, toothpaste, a new TV—to your door, right now. To make it happen, the sellers are revving up supply chains that rely on algorithms of military-grade complexity and workers (human and robot) who roam vast distribution centers 24/7. The trillion-dollar online shopping economy is about to get bigger—and a lot faster.