Big Data Is A Big Deal

The article, “Why ‘Big Data’ is a Big Deal,” written by Jonathan Shaw gives its readers an idea of just how “Big,” big data is. It is transforming the world around us, and helping us make sense of things that were once mind-boggling. Big data is changing the world we live in.

Following his article, there are a series of comments and arguments in response to Shaw’s words. Many of those comments seem to be about how big data can influence matters of security and privacy. While this may be true, I believe the benefits of utilizing big data science outweigh the costs. In order to understand why, we must understand how “Big,” big data really is.

We can gather and access data from just about everything we use; our mobile phones we use daily, our televisions, our iPads and tablets, the trains we take to work, and the airplanes we fly in to go home for Thanksgiving. We have access to so much data…everywhere. This is truly amazing, and the thought of how much data this is, is mind-boggling.

However, as noted in this article, it is not the quantity of data that is revolutionary but the fact that we can now actually do something with the data. In his article, “Why ‘Big Data’ is a Big Deal,” Jonothan Shaw explains to his readers that what once took a $2-million computer to analyze, we can now do the same on merely our personal laptops.

Shaw explains the “Big” roles big data science plays in our great big society, as a whole. Big data science is applicable to nearly every academic discipline and industry: astronomy, physics, energy, medicine, business, government, design, policing and human evolution.

It is also applicable to our daily lives. For example, credit card companies mine data to help evaluate our risk of default. Target used an algorithm to decide what types of coupons to send out. Netflix and Amazon use recommendation engines to show us what we might like to buy, and what we might like to watch; and usually (at least according to my own experience), they are right.

Perhaps the most astounding way we can use big data is to analyze the human race… through social media. There are roughly 2 billion posts each day. This is the greatest increase in the capacity of humans to express themselves in all of human history. We have now developed tools to help us analyze these texts… even in Chinese.

Even though so much data exists, this does not mean we can make sense of it. Shaw gives the example: you can’t just throw it all against the wall and only analyze what sticks. Right now data mining is often considered an industry of its own. It takes data scientists, with specific skill sets to make sense of all this data.

They enable the understanding of data sets using visualization. They aggregate, filter and cluster the data so a person can make sense of it. It cannot be denied that humans are better at seeing patterns than humans are. Therefore, we can combine what humans are good at (asking the right questions and interpreting results) with what the computers are good at (computation, analyzation, and statistics using large datasets). For now, however, it is only the data scientists that are trained and able to do this. Yet big data has a transformative impact on nearly every aspect of our lives.

For this reason, there are new data tools being implemented in higher education. Last fall, there was a Harvard course in data science that attracted more than 400 students (I hope they had a big lecture hall). Student projects included the distribution of tweets for competitive product analysis, predicting the stock market, and the performance of NHL hockey teams.

It certainly will be interesting to see where the rise in big data science takes us in the future. It is proven that data science, analyzation and consulting can and does improve all aspects of life, and especially all businesses. If you are interested in reading the full article, you can do so by clicking Here.

If you are interested in learning how big data tools and big data science can help your company, contact us at Cliintel, by clicking Here.