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Big data – buzz word or businesses’ wildest dream?

What exactly is big data? What is a petabyte? Why does it matter to a small business or independent contractor, and is it just a buzz word or is it a marketer’s dream?

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What is big data?

“Big Data” is defined as large data sets which cannot be managed with simple, common software that captures and processes the data, and is typically consisting of at least dozens of terabytes in a single data set. The challenges of big data are, well, big. It is described by Gartner analyst, Doug Laney1 as being three-dimensional, i.e. increasing volume (amount of data), velocity (speed of data in/out), and variety (range of data types, sources).

The term is being leveraged in conferences across the globe, but most are talking about the challenges of big data as it pertains to social networking sites like Facebook or location based services like Foursquare, and the idea of the volume of data being collected on every single person and how that data is becoming so large that it is a logistical challenge to manage and harvest with any meaning.

In fact, big data was a popular theme at the recent South by Southwest Conference in Austin, with technologists and marketers bringing their unique backgrounds to the conversation, each addressing the collection of and processing of the unprecedented data being collected, for the first time outside of the government, and the concerns that go along with consumers blindly offering up the data.

How BIG is big data?

Strictly speaking to social data, consider for a moment that in a 60 second period, 23,148 apps are downloaded from the App Store, and 208,333 minutes of Angry Birds is played via smartphone3. Additionally, over 28,000 text messages are sent every second, and the average mobile phone user has 736 pieces of personal data collected every day and service providers store this information for one to five years3.

The University of Nebraska physics department4 has 1.6 petabytes of data – that’s 1.6 million gigabytes in one department at one school. Boeing jet engines can produce 10 terabytes of operational information for every 30 minutes they turn4.

Twitter produces 20 gigabytes of data every day

Twitter serves more than 200 million users who produce over 800 tweets per second, each of which is roughly 200 bytes in size4, so on an average day, this traffic equals over 12 gigabytes, and throughout the Twitter ecosystem, the company produces a total of eight terabytes of data per day, compared to the New York Stock Exchange’s single terabyte of data daily.

Like a Boeing jet records every move, every time you interact with Facebook, it records data. It stores information on who clicks what and not just the name of the person, but that person’s profile information like hobbies, high school, family members, ethnicity, religion, employer, etc. Then, that data connects that one click with all other clicks you make within Facebook or any website with the Facebook plugin. That is a lot of information to store for a few simple clicks, especially given how much more demographic information is recorded and tracked than Twitter which creates 20 times the amount of data in a single day than the NYSE.

What to do with the data?

The big challenge behind the scenes is how to process and manage this volume of information in an era where consumers voluntarily offer thousands of data points through social networks, smartphones and the like. Social data is where the buzz is at conferences, but it is being referred to solely as big data, which clearly is much more complex than just what someone clicked on Facebook.

IT expert, Andrew McCafee recently shared the story5 of an Allstate-sponsored contest wherein a small team of data scientists quickly achieved a 340 percent improvement in Allstate insurance’s ability to predict bodily insurance claims based on car characteristics – without any expertise in insurance or automobiles, and without consulting Allstate’s well paid mathematicians who build and maintain these prediction models.

McAfee asks, “So how can it be that a small team of people who don’t even work for the company was able, in three months, to achieve a 340% improvement over Allstate’s ability to predict bodily injury insurance claims based on car characteristics? And how was the team able to do this while working only with disguised data — without, in other words, knowing the true makes and models of the cars? Welcome to the weird new world big data.”

What this means for business

All of the social data collected in recent years is finally becoming useful for more than buying a Facebook ad. True demographics are now evident, but moreover, real consumer behavior is being studied based on tremendously large amounts of data. If just one simple text message records a dozen pieces of data, imagine the depth of information a Facebook user transmits in a single day, with all of their personal data attached to each move.

Social data (or big data) is a nightmare to manage due to the sheer volume and velocity of transmission, but for businesses, it means a legitimate understanding of consumer behavior, not just what someone shared during a focus study or web poll, but really being able to track and understand how each consumer ticks. What’s next is being able to translate that behavior into an isolated profile of a specific type of buyer – this is the kind of data that marketers’ have been dreaming about for decades.

13D Data Management PDF
2Mobclix study
3How phone carriers track private data
4Information Management study
5Allstate prediction model

Lani is the Chief Operating Officer at The American Genius - she has co-authored a book, co-founded BASHH and Austin Digital Jobs, and is a seasoned business writer and editorialist with a penchant for the irreverent.

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33 Comments

33 Comments

  1. Matthew Hardy

    March 19, 2012 at 6:53 pm

    > consumers blindly offering up the data

    > … to translate that behavior into an isolated profile… marketers’ have been dreaming about for decades.

    Remember Soylent Green? Big data is us. 😉

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China no longer dependent on U.S. for smartphone components

(TECH NEWS) Trump’s trade war, more specifically, the ban on shipping phone components, to China has begun to take a toll on chip manufacturing.

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Once upon a time, the U.S. and China were buddies, exporting and importing from each other with ease. However, President Trump’s recent actions regarding trade with China is certainly putting a damper on things.

It seems that Chinese companies have moved past the need to import certain products, like smartphone chips, from the U.S. – something they previously relied heavily on by working with American companies like Qorvo, Inc. in North Carolina, Skyworks, Inc. in Massachusetts, Broadcom, Inc. in California, and Cirrus Logic in Texas.

Since the ban in May, Trump specifically barred shipments from the U.S. from companies like Qualcomm and Intel Corp to companies like Chinese tech conglomerate, Huawei Technologies Co. But much like the bans that came before the Trump administration, it didn’t last long. With tensions high, the U.S. actually recently started rolling back some aspects of the ban and started making exceptions that allow American tech companies to continue to work with Chinese companies like Huawei.

Of course, China’s lack of U.S. parts hasn’t stopped them from rolling out new and improved products. As a matter of fact, in September, Huawei unveiled its newest phone, the Mate 30, which boasts highly-desired features, such as a curved screen and a wide angle camera. This makes the phone a pretty solid competitor of Apple’s newest iPhone, the iPhone 11, of which China was sent 10 million of in September and October.

After Huawei’s announcement, investment and banking firm UBS, and Japanese technology lab Fomalhaut Techno Solutions, partnered up and took to their labs to analyze the phone’s components. Their analysis was simple and straightforward. They found that there were absolutely zero American components in the phone. In fact, the chips in the Mate 30 are actually from Huawei’s in-house chip design agency, HiSilicon. They also provided Huawei with WiFi and Bluetooth chips. With HiSilicon’s 20 + years experience in the industry, 200+ chipsets, and 8000+ patents, it’s no wonder U.S. chip companies are getting nervous. Qualcomm, for example, announced a 31-40% decrease in estimated chip shipments over the next year.

Although the chip ban has made a big impact on larger U.S. companies who make and supply chips to China, there are still many other businesses that have been affected in Trump’s trade war. As it happens, U.S. Commerce Secretary Wilbur Ross recently confessed that, since May, when the ban was put in place, the U.S. has received at least 260 requests, asking that they excuse them from the ban and be allowed to work with China as they previously had.

But really, at the end of the day, with so many American companies relying on China for both import and export, it’s probable that the ban will be short-lived and that exceptions won’t need to be made. As Americans, we can be hopeful that the end-result of this trade war will be a positive one, but only time will tell.

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AI cameras could cut down traffic deaths, but there may be flaws

(TECH NEWS) Traffic accidents have plagued humanity since motor vehicles were created, can AI help cut down on text and drive incidents?

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AI camera

What if we told you Australian officials believe they have found a way to reduce driving deaths by almost 30% in just two years? It’s a pretty appealing concept. After all, Australia alone faces an average of over 3 deaths a day due to driving accidents. And Australia’s average death rate clocks in at just half of what we face in the United States.

There’s just one problem with Australia’s proposed solution: it’s basically Big Brother.

Basically, Australia plans to use AI cameras to catch people texting and driving. There are plenty of places that have outlawed texting and driving, but that rule is very hard to enforce – it basically means catching someone in the act. With AI cameras, hands free driving can be monitored and fined.

Australia has already started rolling out some of these systems in South Wales. Because this is a new initiative, first time offenses will be let off with a warning. The following offenses can add up quickly, though, with fines anywhere from $233 to $309 USD. After a six month trial period, this program is projected to expand significantly.

But there are real concerns with this project.

Surprisingly, privacy isn’t one of these worries. Sure, “AI cameras built to monitor individuals” sounds like a plot point from 1984, but it’s not quite as dire as it seems. First, many places already have traffic cameras in order to catch things like people running red lights. More importantly, though, is the fact these machines aren’t being trained to identify faces. Instead, the machine learning for the cameras will focus on aspects of distracted driving, like hands off the wheel.

The bigger concern is what will come from placing the burden of proof on drivers. Because machine learning isn’t perfect, it will be paired with humans who will review the tagged photographs in order to eliminate false positives. The problem is, humans aren’t perfect either. There’s bound to be false positives to fall through the cracks.

Some worry that the imperfect system will slow down the judicial system as more people go to court over traffic violations they believe are unfair. Others are concerned that some indicators for texting while driving (such as hands off the wheel) might not simply apply texting. What if, for instance, someone was passing a phone to the back seat? Changing the music? There are subtleties that might not be able to be captured in a photograph or identified by an AI.

No matter what you think of the system, however, only time can tell if the project will be effective.

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Tech News

DeepComposer: AWS’ piano keyboard turns AI up to 11

(TECH NEWS) Amazon has been busy with machine learning, which includes a camera, a car, and now DeepComposer that’s able to add to classics on the fly

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Musicians, listen up, there’s a new kid in town, its name is DeepComposer and it’s coming to take your creativity and turn it up to 11.

Artificial Intelligence has taken a leap into what has long been considered the “pinnacle of human creativity”, as Amazon revealed what is said to be the world’s first machine learning-enabled keyboard capable of creating music.

Amazon unveiled its AWS DeepComposer keyboard Monday during AWS re:Invent, a learning conference Amazon Web Services hosted for the global cloud computing community in Las Vegas.

Demonstrating DeepComposer’s abilities, Dr. Matt Wood, Amazon’s VP of Artificial Intelligence, played a snippet of Beethoven’s “Ode to Joy” and then let the keyboard riff on it with drums, synthesizer, guitar, and bass, sharing a more rockin’ version of the masterpiece.

Generative AI, is considered by scientists at MIT to be one of the most promising advances in AI in the past decade, Wood told the crowd. Generative AI allows for a machine not only to learn from example, as a human would but to take it next level and connect the dots, making the next creative step to composing something completely new.

“It [Generative AI] opens the door to an entire world of possibilities for human and computer creativity, with practical applications emerging across industries, from turning sketches into images for accelerated product development, to improving computer-aided design of complex objects, Amazon said on its AWS re:Invent website.

How does it work? The Generative AI technique pits two different neural networks against each other to produce new and original digital works based on sample inputs, according to Amazon. The generator creates, the discriminator provides feedback for tweaks and together they create “exquisite music”, Wood explained.

A user inputs a melody on the keyboard, then using the console they choose the genre, rock, classical, pop, jazz or create your own and voila, you have a new piece of music. Then, if so desired users can share their creations with the world through SoundCloud.

This is the third machine learning teaching device Amazon has made available, according to TechCrunch. It introduced the DeepLens camera in 2017 and in 2018 the DeepRacer racing cars. DeepComposer isn’t available just yet, but AWS account holders can sign up for a preview once it is.

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