Big Data has become very popular and therefore is being made into a “hype”. The Big Data hype gives the impression that Big Data is a magical tool that can be implemented into any company and voila!- instant solutions to all problems. Society has started to place unrealistic expectations on Big Data and the results it can produce.
It is human nature to project our interests onto others. Like the football dad who never made it to the big leagues, companies also place their desires into their data. This is why studies and surveys are supposed to be objective, because as soon as someone biases the data, the results are compromised. Big Data takes a long time to be analyzed properly to find relationships that can be translated into valuable information. When companies jump at the first correlation because it is in line with their desired result is when Big Data becomes biased.
It is extremely important to ensure your data is clean, or else it is going to lead to a lot of wasted money. Companies buy into the Big Data hype, purchase expensive big data technologies and hope that it is going to magically reaffirm all of their dreams and provide a golden staircase to them. This is not how it works.
Big Data is essentially a lot of information. When looking at a lot of information you cannot form a conclusion by simply looking at a portion of it. You must consider every piece of information and how it fits together. This is where Data science comes in. Many are moving away from the term “Big Data” because of the hype surrounding it and are embracing data science. Data science speaks more to the volume of analytical scrutiny big data must go through to provide any useful and unbiased results.
This is why we have data scientists, they are the geniuses who can look through mass amounts of data and find correlations without biasing them. If a company is going to spend the money on implementing big data they must also hire data scientists if they hope to profit from their investment.
The take home point to this would be that companies must allow the data to create new ideas and not try to drive the data with their own thinking.