In business there seems to be a debate on where BI ends and Big Data begins.  Here is an easy way to figure it out.  Start by thinking backwards.  This means think first about the decision that needs to be made, the nature of it, the data that may exist to support it, where the data is, and how you might analyze that data in order to arrive at an answer.  Looking at these attributes will help you understand where BI ends and Big Data begins.  

Transient

Is the decision to be made new?  Not always true but generally BI is about updating old data, models and answers or perhaps taking a small tangent on old data and models to seek new answers.  Big Data is more about solving something that eluded previous analysis. 

Lot of BI is inwardly focused - running the trucks on time and so forth.  Big Data looks to focus on the outward.  Things like regulation, competition, advances in science & technology and so on.  Which leads to the 3rd question to ask - does data already exist that you can feed into your analysis?  For BI the data is mostly lying around inside the company.  For Big Data the data is the fire hose of social media, lots of news feeds and / or a collection of API feeds you have never looked at before.

An intuitive understanding of what to do to the data once you have it is another hallmark of BI vs Big Data.  BI is about traditional well understood analysis.  Big Data is about machine learning - discovering what the underlying patterns, connections and models are without deciding that ahead of time.

The biggest bugaboo is whether the data is structured of unstructured.  As a general rule for BI this means the data is numerical where the unstructured stuff is messy text - written information that conveys essential ideas in a million different ways.

Answer the questions in the chart and you'll know how to proceed.  

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