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Big PrivacyOpen DataTransformation

From Data Collection to Data Use — Big Data

Big Data Transforms the focus of Computing Science From Data Collection to Data Use

Big Data can add new value to collected information in the form of business intelligence. It all depends on how we engage with it. Big Data can be an overwhelming jumble of random snippets of information. But, if we know how to approach it with the right questions – the right “Why?” – Big Data can transform how we use information.

Computer technology has completely revolutionized many aspects of doing business. Computing devices have become so necessary that companies are now dependent on them. We’ve learned to master data collection and retention, and statistical reporting.   The next wave of technological innovation, Big Data, marks a shifting paradigm: from how we collect and retain data to how we use it.

Big Data signifies a radical change in what we can do with electronic information

Over its 50-year history, computing has focused on increasingly complex methods of information collection and retention. Structuring information has also been a priority. We’ve learned how to structure data in byte language, zeros and ones. We’ve created simple structures, called files, to capture serial data. With databases, we’ve improved the structural organization of information to allow for random, or indexed, insertion and retrieval. The primary goal was to ensure consistency – to know that, given a certain input, the computing system could always reproduce the expected output. Computing has been highly valuable for business, in terms of operational viability and efficiency. But value isn’t necessarily added to the content itself – essentially, what you collect is what you retain and export. Now, with the advent of Big Data, things are changing.

From a business perspective, Big Data is a knowledge network, with multiple data elements about consumers from multiple sources: massive in size, and constantly growing and changing. It includes vast amounts of information gleaned by web bugs and cookies tracking online browsing and purchasing habits, but it also incorporates records of consumers’ offline habits; tracking shoppers through malls by their smartphone MAC address, for example. It’s a whole new ballgame, requiring new organizing and analytics technologies, and new storage facilities, such as the cloud.

Now, once multiple data streams are aggregated, collected information can be used in a very different format, adding new value in the form of business intelligence. Big Data allows us to uncover hitherto-unseen patterns or trends that can improve profitability.

Big Data can help us make better use of the information we’ve collected and stored

Let’s give an example of how Big Data works. It’s flu season in Canada, and pharmacies don’t want to run out of Nyquil and Cold FX. Ten years ago, deciding how much extra product to order was based on static data analysis, but now, with Big Data analytics, it’s become remarkably behavioral. Not only can pharmacy chains utilize public health announcements as to projected numbers of flu cases, but they can also analyse tweets by geographical location to see, in real time, how many people are using words like “flu,” “cough”, and “cold.” By coupling these data streams with city stats giving demographic trends for different neighborhoods, drug stores can predict with a good deal of accuracy how many extra bottles of Nyquil to ship to individual stores. By asking the right questions of Big Data, pharmacies can learn, for example, that they should increase supply levels by 10% in the next two weeks for specific postal codes. This information could only have been gleaned from the aggregation of multiple data sources.

The diagram here shows that the focus of big data is to help us create better uses of data

Big Data’s potential advantages, in fields as diverse as marketing and public health, are significant. Such analysis, however, is dependent on the quality of the data elements it connects, and there can be serious privacy issues. These remain as yet largely unaddressed. Big Data doesn’t help us understand how to disclose information. All aspects of the privacy field, from regulation to software, must adapt to this new and challenging reality.

We’ve spent the last 50 years learning how to collect and retain electronic information. Now, with Big Data, we’re starting to use that information in radically new and innovative ways.

 

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