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Technology Trends: Big Data - Executive Leadership Articles

Technology Trends: Big Data

Executive Leadership Articles

Technology Trends: Big Data

By now, you are aware of big data and its ubiquitousness in every aspect of our lives. Every credit card purchase, Facebook “like,” coupon redemption, and web search is being logged somewhere so that someone might make a reasonable prediction about you individually or about some demographic of which you are part. Your active participation isn’t even a requirement anymore in contributing to big data: live, real-time traffic reports on the morning news tell us how fast traffic is moving on our commutes to work, data that’s an aggregation of thousands of cell phones, including yours, simply telling transmitter towers and satellites where your phone is at any given moment.

Big Data is Already Here…
“The new techniques for collecting and analyzing huge bodies of data will help us make sense of our world in ways we are just starting to appreciate,” say Viktor Mayer-Schonberger and Kenneth Cukier, authors of Big Data: A Revolution that will Transform How We Live, Work, and Think (Mariner Books, 2013). Insisting they are big data’s messengers, and not its evangelists, they provide illustrations of how big data is changing the way business is done in fields ranging from retail sales to disease control, offering three qualities of big data that make it the powerful force it is: it’s immediate, there’s more (and more) of it, and it has an almost inherent messiness that would be a headache for statisticians but offers a strangely dynamic accuracy that old statistical methods could not approach.

Big Data is Now
One example the authors offer for big data’s immediacy is the way Google, based on a dataset of millions of search requests, can predict what you’re searching for after just a few keystrokes, constantly updating its prediction based on what you’re typing at any moment and comparing it to its gigantic collection of searches by others. Taking the use of this data a step further, a deep look at what people are searching for in specific areas of the country can reveal where the flu is spreading, and how quickly.

Previous models used by the Centers for Disease Control involved the collection of data from hospitals and then an analysis of that data. By the time the data was collected and models for the spread of flu produced, the data was two weeks old, an enormous amount of time for something whose status changes so quickly. Preventing the spread of disease is difficult when the virus is two weeks ahead you, but Google’s power to correlate what people search for on the Internet right now with flu diagnoses in specific regions changes the medical field’s ability to respond.

Big Data is Big
Big data’s vast size is another advantage over other statistical sources. A random sample of an appropriate size can be a statistical goldmine of predictive information if someone is looking for causes and effects, but where statistics are a predictive science, big data is a correlative exploration: rather than creating hypotheses and then testing them based on a sample set of random data (a difficult, time-consuming goal itself), those who study big data simply look for correlations without explanations. When people do A, B, and C, correlations can be drawn to probable conclusions D and E; the data is its own evidence, whether there is a real-world, sensible bridge between correlations. This means simply identifying relationships vs. looking for causality.

Big Data is Messy
In May 2013, photo hosting website Flickr increased its storage quota for non-paid accounts to a whole terabyte of space, an effectively limitless account for the majority of its 89 million users, some of whom “tag” their eight billion photos with descriptive words. The number of photos on Flickr is so enormous that even if only a small percentage of users tag just a small percentage of their photos, a search for photos tagged “jubilation,” for example, yields hundreds of results. The fact that the data is tainted by people who misspell the word or tag photos with “jubilant” or “jubilee” or some other synonym is expected but doesn’t hurt the likelihood of an appropriate photo being located.

Mayer-Schonberger and Cukier use this concept of tagging data as an example of messiness adding to the richness of searches. When multiple tags can be applied to a photo, search results can be winnowed until something resembling a desired photo is located. Gigantic strides in the computing power accessible by everyday people mean that huge, messy datasets aren’t an obstacle; where once “faulty” data could contaminate a dataset, it can now be included for whatever value it might have in some other relevant search. There’s a reason other social web services have embraced the clickable searchability of hashtags, and making searches easy for its users is only a small piece of that. The value added to datasets with these meta-conversational tags for those who might know what to do with it is increased enormously, especially for non-textual data such as photos.

…and There’s More to Come
The impressive thing about big data is that it doesn’t know what any of the presuppositions are in any analytical field. It doesn’t have a gut instinct and it doesn’t care who the experts are or what they say. All it does is present itself so that nobody knows yet what it can reveal, or what behavior it’s up for predicting based on its own huge self. There’s no way to tell how many problems, solved for ages in some hard, inefficient way, will become easy and inexpensive when approached with the right insight wielding the right data. Crimes will be prevented, accidents avoided, trends spotted, and insanity-causing road traffic alleviated, just for starters.

As this new concept expands, there will be a need for people who know what to do with it, for people who know how to hang onto it, for people who can identify value where others overlook it, for people who can recognize its risks to societal health and individual privacy, and for people who will stand between it and its still-unknown side-effects. It’s a quickly expanding and evolving force, this big data, and it’s unlikely to go away anytime soon.

 

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Technology Trends: Big Data - Executive Leadership Articles

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