In a nutshell, text analytics makes use of the traditional way of data mining and identifies keywords, phrases, or words that can be linked to each other. It is a tool useful in looking for sentiments, relevance, or emotions. It sifts through emails, blogs and more taking unstructured data and linking it with structured ones.
In small data analytics, the focus or range of the searches are naturally small. Most of the data in small data analytics is structured. It allows the researcher to find data in an information pool. For many companies, this is the first step to take. It’s like walking – to do it, you have to learn to take one step at a time. Learning the ropes in small data analytics can be a great preparation before moving on to big data analytics.
Big data analytics is no longer a pool of information – it’s an ocean. In small data analytics, searching for patterns is easier since the pool can be easily explored with values that target information which a researcher already knows is there. In big data, you have to deal with huge databases of information in many forms and more often than not, a researcher has no idea what’s in it or what’s not. In this way, the chances of finding a new trend or pattern is exponentially higher since big data analytics was built in order to do just that. Make connections or links using all the coded algorithms and see what comes out.
In comparison managing small data is easier than big data. Information in small data can be relatively limited while in big data it is virtually unlimited. Both deliver information in short amounts of time making research faster but of course both have its differences.
For companies, taking advantage of small data opens doors to what you already have and finds ways you can potentially profit from it. Big data opens doors to a whole new arena of what is out there. On one hand, big data allows you to be ahead of the game in what could be the next big thing in medicine, fashion, education, engineering, etc. On the other hand, it can help in searching for fraud, security discrepancies and more.
The bottom line is that both techniques are equally useful. Going from small data to big data is like going from the basic level to an advanced level in gathering information that can influence your company’s future business decisions.