Is Big Data Changing The Business You Are In Without You Realizing It?

Throughout my career, one of the primary ways to classify a company has been its industry. Knowing a company’s industry gave you a solid start on understanding the company. From an analytics perspective, you could make highly accurate assumptions about what data an organization would have, what problems it was trying to solve, and what types of analytic processes would be beneficial for the organization’s business.
I have noticed a trend forming where these historical industry classifications and associated assumptions are becoming less and less accurate. I believe that this trend is tied in large part to the rise of analytics and big data over the past few years.
Consider Nike
Much of the general public still thinks that Nike is a clothing manufacturer. However, recent innovations at Nike tell a very different story that many consumers have not come to recognize. Nike is now in the business of collecting, storing, and analyzing data for its customers.  It isn’t unique to Nike. The same phenomenon is being repeated in one way or another at many other companies.
Consider the Nike+ product line and specifically the Nike+ FuelBand. While the FuelBand is being sold and marketed by what many perceive to be a “clothing company,” it really isn’t clothing at all. It is an electronics product. Yes, Nike is in the high tech manufacturing business. The product also has associated web and smartphone applications. Nike is also in the software business. But wait, there’s more! The primary purpose of the device is to capture data on your daily activity such as how many steps you take and if you meet your daily activity goals. That data gets uploaded and stored by Nike. Nike is in the data collection and storage business. How do users interact with their data? Through reports and charts within the associated applications. Nike is in the analytics as a service business.  And some might argue they are in the health business as a result of their analytics.
By now you should get the point. Based on the above, it is clear that Nike is no longer purely in the clothing business.  In fact, they are in several businesses that have nothing to do with clothing and that have completely different challenges. What led to Nike’s success in the past won’t apply directly in these new spaces. Whether or not you’ve realized this change, Nike certainly has. Nike has been steadily developing these new capabilities as it pushes to realize its vision, which is “To bring inspiration and innovation to every athlete in the world.”
What Industry Is Your Company Really In?
There is one critical nuance that needs to be understood. The fact is that consumers won’t choose to buy the Nike+ FuelBand because it is the most fashionable or the most comfortable. Consumers will choose the FuelBand if it offers the most complete data, the best tracking reports, and the best interactive apps. The success of the product will have nothing to do with fashion or clothing at all. Rather, it will have everything to do with data and analytics. Nike knows this and has successfully transitioned to support the requirements of the new product lines.  As the ability to capture, analyze, and distribute data continues to permeate more aspects of our lives, more and more businesses will end up entering into market spaces they would not have dreamed of a few years ago.
Are there areas of your business that are really more about capturing data and using it for analytics than the underlying product itself? If so, it is important to recognize that fact and to adapt your business accordingly. It would be a critical blunder to continue to focus on what your company used to be, or what customers still perceive it to be, rather than to focus on what will actually drive your products’ success in the future. That success may have little to do with the industry you’ve traditionally been a part of.
Nike FuelBands are selling like hotcakes and consumers don’t care that what they may still consider a “clothing company” is selling the product. What those same consumers may not have taken time to realize is that Nike isn’t just a clothing company anymore. Is your organization missing the chance to make a similar transition that challenges the notions of what industry you are in?

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The Datification of Our Daily Lives

Although the term is ugly, “datification” is rapidly becoming a big trend in our daily lives.
Datification is about taking a process or activity that was previously invisible and turning it into data. That data can then be tracked, monitored, and optimized, leading to new opportunities — and new challenges. It’s similar in some ways to the notion of “dark data” –  data that has been ignored up until now because of technology limitations. Only in this case, it’s more like “dark activities” that are now being pushed into the light.
New technologies have enabled lots of new ways to “datify” our normal activities.
For example, my exercise is now datified. I went for a run this morning, and my Fitbit One device recorded exactly how long I ran for, how many strides I took, and how many calories I burned in the process. For the first time, it’s very easy for me to track and monitor my exercise progress.

And that’s just one small example. A lot of my daily activity is now automatically tracked. My network of friends is now datified with Facebook. My network of professional connections is datified with LinkedIn. My location is datified with Foursquare. My latest random thoughts are datified on Twitter. My music preferences are datified with Spotify.
Even reading books is now datified. While I’m reading on my Kindle device, it’s actually watching me. Amazon tracks my reading data and uses it to provide useful services. For example, it knows what page I’m on, so I can easily switch between different devices. It uses my reading speed to estimate how long it’s going to take me to finish a book. And they’ve incorporated some aspects of the wisdom of the crowd idea – for example, I can choose to see which passages other people have highlighted as the most interesting.
That data is also being collected and analyzed by Amazon to optimize book sales. For example, when I recently finished a book in a series by Ken Follet, I received an email the very next morning, giving me a special offer on the next book in the series (interestingly, at a price that was higher than the current “normal” price…)
Amazon can, and probably will, do lots of other things with this data in the future. For example, they could work with authors to help them optimize their books, showing them which passages people find hard to read, or identify at which pages readers tend to give up on the book.
Datification is also rampant in the business world. For example, most commercial vehicles now use GPS to track and optimize journeys. Even tires are becoming datified: Pirelli has embedded sensors into truck tires that constantly beam back information about the tire pressure and temperature, and this is used to calculate tire wear, helping lengthen the lifetime of the tire and optimize preventative maintenance.
We can expect to see much more datification in the future: it makes a huge amount of sense to datify our health, for example – soon, we’ll all be wearing sensors that track our temperature, pulse, blood pressure, and so on. Doctors will be increasingly able to advise treatments not to cure us, but to prevent us from getting sick in the first place.
Education is rapidly being datified with services such as the Khan Academy. This includes the notion of “flipping” education – the pupils watch lecture videos as the homework, and do the exercises in class, where a teacher can monitor what each pupil is struggling with, and intervene as necessary, in a very individual way.
In conclusion, I believe we’ve barely scratched the surface of what is possible. As the price of connected sensors plummets, we’re going to see many other activities being datified. Rick Smolan, the journalist behind the book “The Human Face of Big Data” calls this “creating a nervous system for the world as a whole”, and datification is therefore a key part of the “big data revolution.”

Original Article : http://smartdatacollective.com/timoelliott/133001/datification-our-daily-lives

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How Big Data Analytics Reveal Your Most Intimate Secrets

Big Data Analytics allow us to automatically analyze digital records such as our updates, photos and ‘Likes’ on Facebook. But did you know that your 'Likes' on Facebook could expose intimate details about you as well as personality traits you might not want to share with anyone? Some things about ourselves we'd rather keep private, right? Most of us don’t openly share with the World sensitive personal attributes such as our sexual preferences, our religious or political views, how intelligent we are, how happy we are with life or whether we consume alcohol, cigarettes or even drugs.

Big Data Analytics of Facebook Likes

However, a recent study shows that it is possible to accurately predict a range of highly sensitive personal attributes simply by analyzing the ‘Likes’ you have clicked on Facebook.  The work conducted by researchers at Cambridge University and Microsoft Research shows how the patterns of Facebook ‘Likes’ can very accurately predict your sexual orientation, satisfaction with life, intelligence, emotional stability, religion, alcohol use, smoking, drug use, relationship status, age, gender, race and political views as well as whether your parents are separated. It is quite scary that those “revealing” ‘Likes’ can have little or nothing to do with the actual attributes they help to predict and often a single ‘Like’ is enough to generate an accurate prediction using logistic or linear regression analyis.
Who would have thought that a ‘Like’ for ‘Curly Fries’ is a strong predictor of a high intelligence - maybe this is a good place to admit that I love curly fries (never thought I would share this publicly). Anyway, here are some of the most predictive ‘Likes’ identified in the study:

• For high intelligence: Curly Fries, Science, Mozart, Thunderstorms or The Daily Show
• For low intelligence: Harley Davidson, Lady Antebellum, Chiq, and I Love Being a Mom

• For Satisfaction with Life: Swimming, Jesus, Pride and Prejudice and Indiana Jones
• For Dissatisfaction with Life: Ipod, Kickass, Lamb of God, Quote Portal and Gorillaz

• For being emotionally unstable (neurotic): So So Happy, Dot Dot Curve, Girl Interrupted, The Adams Family, Kurt Donald Cobain
• For being emotionally stable (calm and relaxed): Business Administration, Skydiving, Soccer, Mountain Biking and Parkour 

• For being old: Cup Of Joe For A Joe, Coffee Party Movement, The Closer, Freedomworks, Small Business Saturday, and Fly The American Flag
• For being young: Body By Milk, I Hate My Id Photo, Dude Wait What, J Bigga, and Because I Am A Girl

• For being gay (male): Kathy Griffin, Adam Lambert, Wicked The Musical, Sue Sylvester, Glee and Juicy Culture
• For being straight (male): X Games, Foot Locker, Being Confused After Waking Up From Naps, Sportsnation, WWE, and Wu-Tang Clan

The thing is, when we click ‘Like’ we want to show our friends on Facebook that we feel positive or supportive of specific online content such as status updates, photos or products, books, music or other individuals such as celebrities. What many of us don’t realize is that by doing so you openly share information about yourself that can then be used to predict other, more personal, attributes that you would not share so openly. We now live in a world where everything is digitalized – were we consume music in digital formats, read eBooks, where we shop online and interact with friends and colleagues in social media. This also means that we leave a digital trail of our life and our preferences, which in turn can make it easy to figure out our attributes and personality traits.
Predicting personality traits and attributes is nothing new. For example, personality questionnaires have been around for a long time and they do accurately predict personality types and traits. However, what was different in the past is that we had much more control over the process – we had to complete the survey or give others permission to use our data. With Facebook ‘Likes’ it is slight different because they are by default publicly available. This means that the information you reveal by clicking on a ‘Like’ button can – by default – be used or ‘exploited’ by others using analytics – some with good intentions others with bad ones.
Commercial companies could use this type of Big Data Analytics to dynamically customize the ads you see on your Facebook page (or in fact anywhere) based on your personality traits. Just think of an online ad for the latest car – for people that are classed as shy, reserved and married the ad might highlight safety and family friendliness, while for an single, outgoing and active person it might highlight the attractive design and sporty drive. More worryingly, governments could (and do) use this type of analysis to identify our political views and how they are shifting. Insights from this can then be used to identify how to target election campaigns, etc.
One problem, of course, is that these predictive models are not perfect – no model ever is. Therefore, not everyone who likes curly fries is automatically highly intelligent. The danger is that we might use the insights from predictive modeling to label people wrongly. I can imagine simple mobile phone apps that would allow you to predict personality traits of your friends using this kind of detail. Would you like that? Do you feel that this type of analysis invades your privacy? Will you think twice about ‘Liking’ anything on Facebook from now on? Let me know what you think…share your views…

Source : http://smartdatacollective.com/bernardmarr/129421/how-big-data-analytics-Facebook-likes-reveal-your-most-intimate-secrets

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Developers Can Now Ship Hard Drives To Google To Import Large Amounts Of Data To Cloud Storage

Google just added a new service to Google Cloud Storage that will allow developers to send their hard drives to Google to import very large data sets that would otherwise be too expensive and time-consuming to import. For a flat fee of $80 per hard drive, Google will take the drive and upload the data into a Cloud Storage bucket. This, Google says, can be “faster or less expensive than transferring data over the Internet.” The service is now in limited preview for users with a U.S.-based return address.
Platforms like AWS and Google’s Cloud Platform are obviously great for analyzing large data sets. As Google software engineer Lamia Youseff notes in today’s announcement, however, “transferring large data sets (in the hundreds of terabytes and beyond) can be expensive and time-consuming over the public network.” Uploading 5 terabytes of data over a 100Mbps line could easily take a day or two and most developers may not even have these kinds of connections.
Amazon, it’s worth noting, already offers a very similar service. It, too, charges $80 per hard drive, but in typical Amazon fashion, the company also charges a per-hour fee for importing the data. Importing a 5 terabyte hard drive to S3, Amazon calculates, will cost an additional $45 for an eSATA drive, which makes Google’s flat-fee service significantly cheaper. While Amazon also allows you to export your data using a hard disk, though, Google doesn’t currently offer this service.

Source  : techcrunch.com/2013/06/18/developers-can-now-ship-hard-drives-to-google-to-import-large-amounts-of-data-to-cloud-storage/

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Giving Employees Access to Big Data Has Big Potential [INFOGRAPHIC]

Infographic by Alteryx

 

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What Is Insight? Is It Visual?

Shall we play a game?
What word can connect all three of these words?

Pine

Crab

Sauce

Here's a picture to give you time to think - be warned though, looking at the picture may stop you finding the answer (more on this below).

Got it? That’s right; ‘apple’ can go with them all: pinepple; crab apple; apple sauce.
There are two ways of coming to the answer:

• Analytic logic: did you run through a series of possible matching words until you found the right association? For example, saying: “Does ‘cake’ work? No. Does ‘cone’ work? No. Does ‘tree’ work? No. Does ‘apple’ work? Yes.”
• Unconscious Insight: did you have a moment of pure insight, where your brain leapt to the right answer? You somehow just knew it, with no conscious thought process?

Humans do both, but the neurological process that drives insight, those amazing a-ha moments we all have, has been little understood until recently.
Neuroscientist Dr. Mark Beeman at Northwestern University is using puzzles and brain imaging to understand how insight works. His team have discovered that when an insight occurs different areas of our brains are active than when we reason analytically. The research has identified that a part of the brain above our right ear (specifically the anterior superior temporal gyrus) emits an intense burst of gamma brain waves when an insight happens. As Dr. Beeman says, “The dendrites – the pieces of the neurons that collect information - actually branch differently on the left and right side, characteristically having broader branching in the right hemisphere, so that each neuron is collecting information from a broader source of inputs and this allows them to find connections that might not be evident otherwise.”
So, here’s objective evidence of association occurring naturally in the brain, making connections between distant concepts, in a flash of insight. It seems that associative technology really does reflect the way that we think when we gain insight.
Interestingly, given all the attention on visualization at the moment, neuroscience research has found that although insights can be prompted by visual cues, the brain activity that generates insight is explicitly non-visual. As Professor John Kounios at Drexel University explains: “At the a-ha moment there’s a burst in the right temporal lobe… but if you go about a second before that there’s a burst of alpha waves in the back of the head on the right side. Now strangely enough the back of the brain accomplishes visual processing and alpha is known to reflect brain areas shutting down.”
In other words just before an insight the brain closes down part of the visual cortex.
“You have all this visual information flooding in; your brain momentarily shuts down some of that visual information – sort of like closing your eyes… so the brain does its own ‘blinking’ and that allows very faint ideas to bubble up to the surface as an insight”. Prof Kounios continues: “Think of it this way – when you ask somebody a difficult question, you’ll often notice that they’ll look away or they might close their eyes or look down. They’ll look anywhere but at a face which is very distracting. If your attention is directed inwardly then you’re more likely to solve the problem with a flash of insight.”
The key point here is that while visualization is very useful and compelling, used in isolation (or too extensively) it’s not the most powerful driver of insightful thinking.
Time for one final game: what word can link these four words?

Class

Casual

Risky

Discovery

Got it? I’m sure you have. So what was it for you, analytic logic or pure insight? If it was insight did you catch yourself looking away so your brain could blink?
Notes: 1) This subject of this blog and the quotes in it came from a fantastic BBC Horizon documentary. 2) I’m aware that the word puzzles in this blog may not be as effective for readers whose first language is not English - I hope that doesn’t undermine its interest for those of you. 3) Distracting image source (creative commons sharealike license).

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