A recent Google search for the term “big data” returned more than 660 million results. There is no doubt that the potential of analyzing large, diverse data sets has created much fanfare.
But what exactly is big data?
David Meer, a partner with Booz & Co.’s consumer and retail practice, recently took on the task of nailing down the definition of big data and how applying data analysis to it can allow business to gain actionable insight.
“Why is this important? Because the amount of data generated by digitization will always exceed our ability to store, process, and make sense of it,” Meer writes in a Forbes blog post. “Most of it is irrelevant noise, so unless non-technical businesspeople are clear about the kinds of data being gathered and how to make practical use of it, they will be overwhelmed.”
Meer separates externally gathered data into two categories: structured and unstructured.
Typically, businesses are familiar with structured data, research surveys, transactional data, ratings and reviews on various websites and other data (like credit scores) that can be stored and manipulated in a database.
“Now let’s talk about unstructured data – information that can’t be easily classified by a numerical rating, click, computer IP address, cookie, or bar code,” Meer notes. “Unstructured data is, of course, where the real explosion in data quantity is happening.
Meer divides unstructured data into two categories: captured and user-generated.
Captured data refers to “information gathered passively from an individual’s behavior, such as search terms you enter and the location data that your phone generates through GPS.” Consumers are not always aware that they are generating this information about themselves, he adds.
User-generated data includes the views of a consumer expressing his opinions by commenting on an online article, writing a blog post, posting to Twitter or Facebook, and posting videos to YouTube. While most of this data is not attributed to a specific individual, it can provide context for product design and marketing communications.
Moreover, the potential benefits from big data often rest with the diversity of the data sets available to analyze rather than the pure size, according to a Harvard Business Review blog post.
For example, retailers have had large amounts of structured data from transactions for many years; this is not new. However, with big data, marketers are only now connecting data from loyalty programs in physical stores with data about how the same customers behave on the company website and across the web.
“They can then link this data with in-depth market research as well as social media data from Twitter or Facebook,” according to the authors of the post. “This kind of linkage is reaping rich rewards. A leading telco company we have worked with was able to increase market share by more than 20% in some countries without increasing the marketing budget by leveraging behavioral and transactional data from social and general media.”
Furthermore, some innovative companies are melding data historically used by banks to assess the credit score of loan applicants with mobile phone usage data and social media data to better assess an applicant’s credit-worthiness.
“Diversity, if managed well, yields divergent thinking and the pooling of a broader base of knowledge results often in better strategic choices,” the post concludes. “So perhaps we shouldn’t be talking about big data making decisions better, but about diverse data connecting the dots using new technologies, processes, and skills. We need to connect the dots or we risk drowning in big data.”
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