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Leaked Snapchat Data Uncovers Surprising Patterns

Lee Clemmer

leaked dataA new year, a new data leak.

On New Year’s Eve an anonymous group or person leaked about 4.6 million Snapchat usernames along with the associated phone numbers, save for the last two digits.

The leak came about a week after Snapchat dismissed the threat – brought to their attention by Gibson Security – in a blogpost: “Theoretically, if someone were able to upload a huge set of phone numbers, like every number in an area code, or every possible number in the U.S., they could create a database of the results and match usernames to phone numbers that way. Over the past year we’ve implemented various safeguards to make it more difficult to do. We recently added additional counter-measures and continue to make improvements to combat spam and abuse.”

Apparently their counter-measures weren’t enough.

Soon after the breach, the alleged hackers responded to requests for comment by The Verge“Our motivation behind the release was to raise the public awareness around the issue, and also put public pressure on Snapchat to get this exploit fixed,” they say. “Security matters as much as user experience does.”  Snapchat CEO responded to the breach in this NBC interview: “We thought we had done enough.”

I examined the data to see if there’s anything we can learn.

What I discovered was something I hadn’t really thought of before, namely information encoded within other information.  A straight-forward example is geographical information being encoded in the first three digits of a telephone number. Looking at usernames, I learned that we humans sometimes include quite a bit of information about ourselves in those usernames – for example our actual, real name.  So a username can be more than just a username.

Let’s start by taking a look at the telephone numbers. We can see what users have been affected by this data breach by taking a look at the area codes of the phone numbers (to see if you are part of the leaked data, you can search for your name here.) As mentioned in various reports, the leaks only affect North American users.  You can find the list of North American phone numbers on Wikipedia: there are 323 American and 41 Canadian area codes.  After loading up the data in R (the application for statistical computing), I split the telephone numbers and counted the area codes.  There are 76 in total, two from Canada and the rest from the U.S. (download CSV here).

Here are the top 10 area codes:

Area Code Frequency State
815 215,953 Illinois
909 215,855 California
818 205,544 California
951 200,008 California
310 196,183 California
847 195,925 Illinois
720 188,285 Colorado
323 168,565 California
347 166,374 New York
917 165,420 New York

Next I fired up SAP Lumira to take advantage of the great mapping features it has (you can get your free copy here).  Here’s a choropleth map showing which states have been affected the most by the leak. If you live in a grey state, you’re not part of the leak.  If you’re in a green state, you may want to check to see if you’re data has been compromised (you can check here). snapchat_leaks_image_1The leaked data also comes marked up with regional information below the state level, which after looking into a bit I’m confident is accurate.  Here are the top 10 regional locations affected by the leaks (download CSV here):

Region Frequency
New York City 334,445
Miami 222,321
Chicago Suburbs 215,953
Eastern Los Angeles 215,855
Los Angeles 209,888
San Fernando Valley 205,544
Southern California 200,008
Northern Chicago Suburbs 195,925
Denver-Boulder 188,285
Downtown Los Angeles 168,565

As this dataset is incomplete, we can only really draw conclusions about what users have been affected by this leak.  Some larger urban areas – like my Philadelphia – are fairly low on the list. I wouldn’t conclude that Snapchat is unpopular there, simply that it wasn’t hit as hard.

Now let’s take a look at the usernames and see what kind of information is contained in those.  To start, we’ll just get a sense of how long these usernames are.  What we get is a nice, nearly normal distribution with a bit of right skew.  Looking at the data, I would guess that Snapchat requires a username of between 3 and 15 characters.  However, there are exactly 5 notable outliers (excluded in the histogram below), users for whom their email address has been published instead of their username (unless these 5 could choose to have their username be their email?).  I wonder how these 5 got to be included in this data set.

snapchat_leaks_image_2A lot of usernames appear to be people’s actual names.  After Googling random ones, it turns out it’s almost trivially easy to start connecting this data to additional information like names, pictures, Facebook accounts, Tumblr blogs, Twitter accounts, etc.

So what are popular names of Snapchat users?  I decided to count how many usernames started with an actual first name.  To get a list of first names to search against, I got a list of popular baby names posted by the Social Security Administration and created a list of the top 50 boy and girl names (so 100 names in total) since 1980.  Next I counted how many times each name occurred at the beginning of a Snapchat username.  Of all Snapchat usernames, about 8% start with a top 100 name. Here’s the top 10 list of most common first names a username starts with:

John
Sarah
Ashley
Emily
Daniel
Ryan
Eric
Brian
Maria
Lauren

Another common pattern in usernames is to append a number at the end of your usernames. How many numbers? Although two digits is the most common number of ending digits, we’ll take a look at four digits to get a better look at years.  What does this distribution look like?

snapchat_leaks_image_4Clearly a lot of numbers other than years are chosen, so let’s zoom into the thick spick around the 1900s.  Also, let’s assume that the years are birth years and then turn the years into age.

Here is a five to 50 age distribution: snapchat_leaks_image_5We see a big spike for age 13, which means many people chose to end their username in the number 2000.  Same for age 44: ending your username in 1969 was unusually popular.  I wouldn’t be surprised if the actual Snapchat age distribution looked similar to this.  We see the biggest change of users ranging in age from 13 to 23, so roughly middle school through college.  Keep in mind, however, that these conclusions are based on a number of assumptions should be taken with a very large grain of salt.

Finally, there are all kinds of other factoids contained in these names.  The word “cat” occurs twice as many times as “dog”.  Lions are twice as popular as tigers.  There are over 5,000 sexy Snapchat users.  And so on.  A username is not just a username, but often tells us a bit more about the person lurking behind that name.

Gibson security has some good advice for those whose information has been compromised: you can delete your Snapchat account, change your phone number, and never give out your phone number if you don’t have to.  The moral of the story is that even super-popular services getting billion dollar buyout offers aren’t immune to user data leaks, so be sure you take your online privacy seriously.

This story originally appeared on SAP Business Trends.

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lclemmer

About lclemmer

Lee Clemmer is a Senior Data Analyst at SAP. He is experienced in providing new reporting and analytics capabilities and services to provide actionable insights that support business goals.

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#Forbes , awareness

Data Analysts And Scientists More Important Than Ever For The Enterprise

Daniel Newman

The business world is now firmly in the age of data. Not that data wasn’t relevant before; it was just nowhere close to the speed and volume that’s available to us today. Businesses are buckling under the deluge of petabytes, exabytes, and zettabytes. Within these bytes lie valuable information on customer behavior, key business insights, and revenue generation. However, all that data is practically useless for businesses without the ability to identify the right data. Plus, if they don’t have the talent and resources to capture the right data, organize it, dissect it, draw actionable insights from it and, finally, deliver those insights in a meaningful way, their data initiatives will fail.

Rise of the CDO

Companies of all sizes can easily find themselves drowning in data generated from websites, landing pages, social streams, emails, text messages, and many other sources. Additionally, there is data in their own repositories. With so much data at their disposal, companies are under mounting pressure to utilize it to generate insights. These insights are critical because they can (and should) drive the overall business strategy and help companies make better business decisions. To leverage the power of data analytics, businesses need more “top-management muscle” specialized in the field of data science. This specialized field has lead to the creation of roles like Chief Data Officer (CDO).

In addition, with more companies undertaking digital transformations, there’s greater impetus for the C-suite to make data-driven decisions. The CDO helps make data-driven decisions and also develops a digital business strategy around those decisions. As data grows at an unstoppable rate, becoming an inseparable part of key business functions, we will see the CDO act as a bridge between other C-suite execs.

Data skills an emerging business necessity

So far, only large enterprises with bigger data mining and management needs maintain in-house solutions. These in-house teams and technologies handle the growing sets of diverse and dispersed data. Others work with third-party service providers to develop and execute their big data strategies.

As the amount of data grows, the need to mine it for insights becomes a key business requirement. For both large and small businesses, data-centric roles will experience endless upward mobility. These roles include data anlysts and scientists. There is going to be a huge opportunity for critical thinkers to turn their analytical skills into rapidly growing roles in the field of data science. In fact, data skills are now a prized qualification for titles like IT project managers and computer systems analysts.

Forbes cited the McKinsey Global Institute’s prediction that by 2018 there could be a massive shortage of data-skilled professionals. This indicates a disruption at the demand-supply level with the needs for data skills at an all-time high. With an increasing number of companies adopting big data strategies, salaries for data jobs are going through the roof. This is turning the position into a highly coveted one.

According to Harvard Professor Gary King, “There is a big data revolution. The big data revolution is that now we can do something with the data.” The big problem is that most enterprises don’t know what to do with data. Data professionals are helping businesses figure that out. So if you’re casting about for where to apply your skills and want to take advantage of one of the best career paths in the job market today, focus on data science.

I’m compensated by University of Phoenix for this blog. As always, all thoughts and opinions are my own.

For more insight on our increasingly connected future, see The $19 Trillion Question: Are You Undervaluing The Internet Of Things?

The post Data Analysts and Scientists More Important Than Ever For the Enterprise appeared first on Millennial CEO.

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Daniel Newman

About Daniel Newman

Daniel Newman serves as the Co-Founder and CEO of EC3, a quickly growing hosted IT and Communication service provider. Prior to this role Daniel has held several prominent leadership roles including serving as CEO of United Visual. Parent company to United Visual Systems, United Visual Productions, and United GlobalComm; a family of companies focused on Visual Communications and Audio Visual Technologies. Daniel is also widely published and active in the Social Media Community. He is the Author of Amazon Best Selling Business Book "The Millennial CEO." Daniel also Co-Founded the Global online Community 12 Most and was recognized by the Huffington Post as one of the 100 Business and Leadership Accounts to Follow on Twitter. Newman is an Adjunct Professor of Management at North Central College. He attained his undergraduate degree in Marketing at Northern Illinois University and an Executive MBA from North Central College in Naperville, IL. Newman currently resides in Aurora, Illinois with his wife (Lisa) and his two daughters (Hailey 9, Avery 5). A Chicago native all of his life, Newman is an avid golfer, a fitness fan, and a classically trained pianist

When Good Is Good Enough: Guiding Business Users On BI Practices

Ina Felsheim

Image_part2-300x200In Part One of this blog series, I talked about changing your IT culture to better support self-service BI and data discovery. Absolutely essential. However, your work is not done!

Self-service BI and data discovery will drive the number of users using the BI solutions to rapidly expand. Yet all of these more casual users will not be well versed in BI and visualization best practices.

When your user base rapidly expands to more casual users, you need to help educate them on what is important. For example, one IT manager told me that his casual BI users were making visualizations with very difficult-to-read charts and customizing color palettes to incredible degrees.

I had a similar experience when I was a technical writer. One of our lead writers was so concerned with readability of every sentence that he was going through the 300+ page manuals (yes, they were printed then) and manually adjusting all of the line breaks and page breaks. (!) Yes, readability was incrementally improved. But now any number of changes–technical capabilities, edits, inserting larger graphics—required re-adjusting all of those manual “optimizations.” The time it took just to do the additional optimization was incredible, much less the maintenance of these optimizations! Meanwhile, the technical writing team was falling behind on new deliverables.

The same scenario applies to your new casual BI users. This new group needs guidance to help them focus on the highest value practices:

  • Customization of color and appearance of visualizations: When is this customization necessary for a management deliverable, versus indulging an OCD tendency? I too have to stop myself from obsessing about the font, line spacing, and that a certain blue is just a bit different than another shade of blue. Yes, these options do matter. But help these casual users determine when that time is well spent.
  • Proper visualizations: When is a spinning 3D pie chart necessary to grab someone’s attention? BI professionals would firmly say “NEVER!” But these casual users do not have a lot of depth on BI best practices. Give them a few simple guidelines as to when “flash” needs to subsume understanding. Consider offering a monthly one-hour Lunch and Learn that shows them how to create impactful, polished visuals. Understanding if their visualizations are going to be viewed casually on the way to a meeting, or dissected at a laptop, also helps determine how much time to spend optimizing a visualization. No, you can’t just mandate that they all read Tufte.
  • Predictive: Provide advanced analytics capabilities like forecasting and regression directly in their casual BI tools. Using these capabilities will really help them wow their audience with substance instead of flash.
  • Feature requests: Make sure you understand the motivation and business value behind some of the casual users’ requests. These casual users are less likely to understand the implications of supporting specific requests across an enterprise, so make sure you are collaborating on use cases and priorities for substantive requests.

By working with your casual BI users on the above points, you will be able to collectively understand when the absolute exact request is critical (and supports good visualization practices), and when it is an “optimization” that may impact productivity. In many cases, “good” is good enough for the fast turnaround of data discovery.

Next week, I’ll wrap this series up with hints on getting your casual users to embrace the “we” not “me” mentality.

Read Part One of this series: Changing The IT Culture For Self-Service BI Success.

Follow me on Twitter: @InaSAP

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Taking Learning Back to School

Dan Wellers

 

Denmark spends most GDP on labor market programs at 3.3%.
The U.S. spends only 0.1% of it’s GDP on adult education and workforce retraining.
The number of post-secondary vocational and training institutions in China more than doubled from 2000 to 2014.
47% of U.S. jobs are at risk for automation.

Our overarching approach to education is top down, inflexible, and front loaded in life, and does not encourage collaboration.

Smartphone apps that gamify learning or deliver lessons in small bits of free time can be effective tools for teaching. However, they don’t address the more pressing issue that the future is digital and those whose skills are outmoded will be left behind.

Many companies have a history of effective partnerships with local schools to expand their talent pool, but these efforts are not designed to change overall systems of learning.


The Question We Must Answer

What will we do when digitization, automation, and artificial intelligence eject vast numbers of people from their current jobs, and they lack the skills needed to find new ones?

Solutions could include:

  • National and multinational adult education programs
  • Greater investment in technical and vocational schools
  • Increased emphasis on apprenticeships
  • Tax incentives for initiatives proven to close skills gaps

We need a broad, systemic approach that breaks businesses, schools, governments, and other organizations that target adult learners out of their silos so they can work together. Chief learning officers (CLOs) can spearhead this approach by working together to create goals, benchmarks, and strategy.

Advancing the field of learning will help every business compete in an increasingly global economy with a tight market for skills. More than this, it will mitigate the workplace risks and challenges inherent in the digital economy, thus positively influencing the future of business itself.


Download the executive brief Taking Learning Back to School.


Read the full article The Future of Learning – Keeping up With The Digital Economy

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Dan Wellers

About Dan Wellers

Dan Wellers is founder and leader of Digital Futures at SAP, a strategic insights and thought leadership discipline that explores how digital technologies drive exponential change in business and society.

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Why Millennials Quit: Understanding A New Workforce

Shelly Kramer

Millennials are like mobile devices: they’re everywhere. You can’t visit a coffee shop without encountering both in large numbers. But after all, who doesn’t like a little caffeine with their connectivity? The point is that you should be paying attention to millennials now more than ever because they have surpassed Boomers and Gen-Xers as the largest generation.

Unfortunately for the workforce, they’re also the generation most likely to quit. Let’s examine a new report that sheds some light on exactly why that is—and what you can do to keep millennial employees working for you longer.

New workforce, new values

Deloitte found that two out of three millennials are expected to leave their current jobs by 2020. The survey also found that a staggering one in four would probably move on in the next year alone.

If you’re a business owner, consider putting four of your millennial employees in a room. Take a look around—one of them will be gone next year. Besides their skills and contributions, you’ve also lost time and resources spent by onboarding and training those employees—a very costly process. According to a new report from XYZ University, turnover costs U.S. companies a whopping $30.5 billion annually.

Let’s take a step back and look at this new workforce with new priorities and values.

Everything about millennials is different, from how to market to them as consumers to how you treat them as employees. The catalyst for this shift is the difference in what they value most. Millennials grew up with technology at their fingertips and are the most highly educated generation to date. Many have delayed marriage and/or parenthood in favor of pursuing their careers, which aren’t always about having a great paycheck (although that helps). Instead, it may be more that the core values of your business (like sustainability, for example) or its mission are the reasons that millennials stick around at the same job or look for opportunities elsewhere. Consider this: How invested are they in their work? Are they bored? What does their work/life balance look like? Do they have advancement opportunities?

Ping-pong tables and bringing your dog to work might be trendy, but they aren’t the solution to retaining a millennial workforce. So why exactly are they quitting? Let’s take a look at the data.

Millennials’ common reasons for quitting

In order to gain more insight into the problem of millennial turnover, XYZ University surveyed more than 500 respondents between the ages of 21 and 34 years old. There was a good mix of men and women, college grads versus high school grads, and entry-level employees versus managers. We’re all dying to know: Why did they quit? Here are the most popular reasons, some in their own words:

  • Millennials are risk-takers. XYZ University attributes this affection for risk taking with the fact that millennials essentially came of age during the recession. Surveyed millennials reported this experience made them wary of spending decades working at one company only to be potentially laid off.
  • They are focused on education. More than one-third of millennials hold college degrees. Those seeking advanced degrees can find themselves struggling to finish school while holding down a job, necessitating odd hours or more than one part-time gig. As a whole, this generation is entering the job market later, with higher degrees and higher debt.
  • They don’t want just any job—they want one that fits. In an age where both startups and seasoned companies are enjoying success, there is no shortage of job opportunities. As such, they’re often looking for one that suits their identity and their goals, not just the one that comes up first in an online search. Interestingly, job fit is often prioritized over job pay for millennials. Don’t forget, if they have to start their own company, they will—the average age for millennial entrepreneurs is 27.
  • They want skills that make them competitive. Many millennials enjoy the challenge that accompanies competition, so wearing many hats at a position is actually a good thing. One millennial journalist who used to work at Forbes reported that millennials want to learn by “being in the trenches, and doing it alongside the people who do it best.”
  • They want to do something that matters. Millennials have grown up with change, both good and bad, so they’re unafraid of making changes in their own lives to pursue careers that align with their desire to make a difference.
  • They prefer flexibility. Technology today means it’s possible to work from essentially anywhere that has an Internet connection, so many millennials expect at least some level of flexibility when it comes to their employer. Working remotely all of the time isn’t feasible for every situation, of course, but millennials expect companies to be flexible enough to allow them to occasionally dictate their own schedules. If they have no say in their workday, that’s a red flag.
  • They’ve got skills—and they want to use them. In the words of a 24-year-old designer, millennials “don’t need to print copies all day.” Many have paid (or are in the midst of paying) for their own education, and they’re ready and willing to put it to work. Most would prefer you leave the smaller tasks to the interns.
  • They got a better offer. Thirty-five percent of respondents to XYZ’s survey said they quit a previous job because they received a better opportunity. That makes sense, especially as recruiting is made simpler by technology. (Hello, LinkedIn.)
  • They seek mentors. Millennials are used to being supervised, as many were raised by what have been dubbed as “helicopter parents.” Receiving support from those in charge is the norm, not the anomaly, for this generation, and they expect that in the workplace, too.

Note that it’s not just XYZ University making this final point about the importance of mentoring. Consider Figures 1 and 2 from Deloitte, proving that millennials with worthwhile mentors report high satisfaction rates in other areas, such as personal development. As you can see, this can trickle down into employee satisfaction and ultimately result in higher retention numbers.

Millennials and Mentors
Figure 1. Source: Deloitte


Figure 2. Source: Deloitte

Failure to . . .

No, not communicate—I would say “engage.” On second thought, communication plays a role in that, too. (Who would have thought “Cool Hand Luke” would be applicable to this conversation?)

Data from a recent Gallup poll reiterates that millennials are “job-hoppers,” also pointing out that most of them—71 percent, to be exact—are either not engaged in or are actively disengaged from the workplace. That’s a striking number, but businesses aren’t without hope. That same Gallup poll found that millennials who reported they are engaged at work were 26 percent less likely than their disengaged counterparts to consider switching jobs, even with a raise of up to 20 percent. That’s huge. Furthermore, if the market improves in the next year, those engaged millennial employees are 64 percent less likely to job-hop than those who report feeling actively disengaged.

What’s next?

I’ve covered a lot in this discussion, but here’s what I hope you will take away: Millennials comprise a majority of the workforce, but they’re changing how you should look at hiring, recruiting, and retention as a whole. What matters to millennials matters to your other generations of employees, too. Mentoring, compensation, flexibility, and engagement have always been important, but thanks to the vocal millennial generation, we’re just now learning exactly how much.

What has been your experience with millennials and turnover? Are you a millennial who has recently left a job or are currently looking for a new position? If so, what are you missing from your current employer, and what are you looking for in a prospective one? Alternatively, if you’re reading this from a company perspective, how do you think your organization stacks up in the hearts and minds of your millennial employees? Do you have plans to do anything differently? I’d love to hear your thoughts.

For more insight on millennials and the workforce, see Multigenerational Workforce? Collaboration Tech Is The Key To Success.

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