In E-Commerce, Small Data = Big Data and Vice Versa
Big Data, small data and everyday data: Is there a meaningful difference between these three information carriers nowadays? The answer by data scientists would be no; some of the information that can be gleaned from Big Data sets these days can also be extracted from smaller data sets.
The real question that should be asked of Big Data is whether the enterprise world is using the right term to describe the future of analytics. The size of data sets is relevant only to a certain extent; it is more important to determine courses of action that should be followed based on the information provided by the data analysis.
Understanding Big Data
In essence, Big Data refers to large amounts of information being transmitted in digital format from various sources. Two sources worth mentioning include websites and point-of-sale (POS) terminals connected to the cloud. The two main data categories being collected are structured and unstructured. Structured data refers to alphanumeric information that has been created by electronic means. Unstructured data mostly refers to images but may also encompass other forms of media such as scanned paper documents, MP3 files, videos, and more.
A fashion designer may think that she does not have any use for Big Data; nonetheless, this opinion quickly changes when she looks at an infographic that highlights the wage gap between men and women working in the fashion industry. Data scientists believe that many business owners underestimate the value of Big Data; this statement is based on the fact that less than 50 percent of companies can confidently say that they are deriving profits from their large data sets.
Big Data, Small Data and E-Commerce
Owners of e-commerce companies are often unaware that they are using Big Data. The owner of an online boutique, for example, could look at her premium Google Analytics reports and order her webmaster to make certain changes beneficial to visitors and conducive to more sales. Unless this boutique is getting millions of visitors each day, the owner made a decision based on small data; however, the recommendation came from Big Data.
Business solutions such as Google Analytics essentially turn Big Data into small data. The results are easy to interpret so that actionable decisions can be made, and this is very important for e-commerce operators.
An example of an e-commerce website that makes good decisions based on small data is SNI’s pharmaceutical sales training, which has been carefully designed after looking at "heat maps" that show how visitors behave when they browse each page and where they are more likely to click. E-commerce giants such as eBay and Amazon, on the other hand, have to base their decisions after evaluating Big Data sets because they get massive traffic on a minute-by-minute basis.
How Small Data is Created
One of the best examples of small data was explained above with the infographic evaluated by a fashion designer. If the salary information was obtained from the United States Bureau of Labor Statistics or from the U.S. Census Bureau, it can be safely said that Big Data insights were slimmed down to small data for the benefit of the infographic designer.
Small data is created by means of software, queries, visualizations, lines of code, and others. The key is to make the data actionable. For example, the fashion designer may be shocked to learn that 70 percent of males working in the fashion industry earn more than she does. This salary gap in terms of gender is something that she can take action on from an activist point of view. Had she looked at the raw data sets of the U.S. Census, she may have reached a different conclusion.
In the end, most business owners will never look at the raw sets of Big Data; they will look at small data sets that will help them grow their e-commerce ventures.
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