The answer is 42, what was the question?

Anyone who is a fan of Douglas Adam's work "Hitchhikers Guide to the Galaxy" (HG2G) knows the concept of the answer to life, the universe, and everything. Even Google will respond with 42 in a calculator if you ask it that question. If you haven't read the book, or seen the movie, you might want to skip this part, little spoiler coming. The concept is that an advanced race of beings built the largest computer in the Universe to answer that question, to which it answered, 42.  The computer pointed out that the beings did not ask the right question. The plot then goes onto create a more powerful computer to ask the right question, and continues to play around with this concept, through the end of the series. All too often do we look toward our data to give us answers, without concentrating on what our questions are. 

This concept, what is the right question, is something that is key to Business Intelligence and Analytics. Often times, we are asked to create something, but the question is not clear, and thus the answer does not make sense. The book series, HG2G, they go on to explore the concept of "garbage in, garbage out" in context to the answer not matching the expectations of the beings attempting to calculate the question. This is quite often the core problem with data in today's world of "Big" data. We have lots of data, but to be honest, most if it is rough, from an analytical stand point. In order to derive true value out of data, it has to be mined, refined, cut, shaped, and tagged, in order to answer a question. 

Often times, we spend time working out visual representations of data that is appealing to the eye, using color and shapes to grab attention, while spending less time on ensuring we are answering the right question. Good visual analytics have a solid basis in a question that is being answered, and illustrate it to users in a simple and easy to digest format.  

The next time you think about making a visual for analytical purposes, spend some time to think about the question that you are answering, and make sure your data and visuals answer that question clearly, without the need for explanations, or a computer built by an advanced race of beings.