Which of the Following Statements is Valid of Big Data Analytics?

“Big Data is Eating Business.” This was a statement made in a recent meeting I attended with some business executives who were already experiencing significant success using big data analytics. What they said made me stop and think. It quickly reminds me of an old joke: “What is the difference between a hunter and a scientist? A hunter hunts; the scientist studies nature.”

which of the following statements is true of big data

Yes, there is a huge difference between the two. However, it does not mean that those in the field of big data analytics are lying to the American people. On the contrary, those executives who bring this specialty to the table to understand that there is a distinction between studying nature and studying human behavior. The former is concerned with understanding natural phenomena, while the latter applies specifically to economics, business, marketing, etc.

So, which of the following statements is valid of big data analytics? A. It analyzes consumer behaviors based on their proximity to a particular retail outlet. B. It analyzes consumer behavior based on their proximity to various other retail outlets.

In a prior article, I explained one of the main reasons why the American consumer’s attitude toward big data is so different than in, say, Germany or Japan. Interestingly, the German consumers expressed more interest in shopping online. The main reason why this was the case was because they were more technologically savvy and had access to better products and services.

Online retailers are beginning to experience a similar trend. Their customers are becoming increasingly demanding. What is it that online retailers can do differently to be able to maintain their edge in the market? There are many things that can be done, but some of them may seem counterintuitive to those who are used to the traditional ways of doing business.

Retail data may well be an extension of customer data. Yet retailers must also remember that they are still running a business. In some cases, the best way to remain relevant is to not be so predictable. As a result, retail data analytics may be a blessing for retailers who are willing to be flexible.

A. Data shows only averages. No matter how detailed or insightful the information may be big data analytics will only give an average result. So to ask “which of the following statements is valid of big data?” would require retailers to first accept that there is no perfect science to retail and then use that as a premise in formulating an action plan.

B. Analytics may point to where changes may need to be made. Just because data is big does not mean that every piece of it is useful information. An example of this is when a retailer has too many products on display and then notices a slight decrease in foot traffic or interest.

C. Data cannot tell if a product is profitable or not. Again, this may require the retailer to ask, “What of the following statements is valid of big data analytics?” While it may be true that big data analytics cannot tell whether or not a product is profitable, it can give the retailer a great idea of what current trends may be leading to. However, trends can change at any time so even if a trend continues to exist, the trend may not necessarily be indicative of a profitability issue.

D. There is too much data. Some analysts have accused big data analytics of being populated by too much data. However, as previously mentioned, trends can shift and so can profit. Retailers should take note that big data is only one tool that they have to use in their business. However, by making sure that they do not get overwhelmed with the volume of data out there, they will better be able to analyze the information that they have.

E. I do not have all the data. This is another common complaint among those who are using big data analytics. However, even if you do not have all of the information needed to make a good decision, the analysis tools available will allow you to make an educated decision. This will help you be better prepared for your decisions when they come.

F. I do not have time/energy to learn more about big data. Again, this is another common complaint among those who are learning about and using big data analytics. However, there is time and energy available. Those who master the tools available to them quickly become empowered with this valuable new tool. In fact, they can often save a company millions of dollars in their profit margins.