Data Informed recently asked Pete Eppele, and a handful of other data experts, one simple question: What is the biggest misconception about big data? Pete’s response:
“From my perspective, the biggest misconception is that there’s more benefit and better ROI available from simple analytics on big data than from more sophisticated, predictive analytics on little(r) data. Managers often think that the next wave of benefit from data-driven decision making comes from amassing and analyzing a huge volume of data from a variety of different internal and external sources. They then start down the path of applying simple analytics to the data set to see what sales or marketing insights they can glean. Simple analytics, particularly when they are backward looking in nature and don’t have the ability to separate true signal from noise, can be confusing and, worse yet, misleading.
Regardless of how large and diverse a data set used in the analysis, simple analytics fail to provide a clear path forward for how to make better decisions in the future. A better approach is to start with the business problem in mind, seek out only the data you need to address it and apply sophisticated predictive and prescriptive analytics to the data. For example, a company’s transaction data that is collected in the course of doing business holds a wealth of signals that can inform everything from inventory decisions to pricing decisions to sales decisions when sophisticated analytics are applied to the data set. The output of those sophisticated analytics is not charts and reports that require interpretation. Rather, the output is forward-looking guidance to make a specific type of decision. This approach offers significantly more benefit at a much lower cost.”
Read the four additional answers in the full article.
Speak Your Mind: What is the Biggest Misconception About Big Data?