We know that the internet has disrupted and changed the shape of how we communicate on a local, national, and global scale. While big data has a lot in common with the internet, it marks something different; the transformation of how we process the information we receive. Over time, big data has the ability to change our thinking and give us a better understanding of many different facets of life and business.
In the past, honing in on smaller pieces of information gave people the ability to really examine it and to come to their own conclusions. However, our technical environment has now changed. We are no longer limited like we were before on the amounts of data we can manage. With the concept of big data, we can use larger samples when doing studies and take into account more subsets.
The History of Big Data
Big data has its roots in the 1980s digital revolution. With the help of microprocessors and computer memory, we were able to store and analyze more data than ever before. With big data, the term “datafication” was coined, which is the term describing all aspects of life turning into data. It’s quite possible that big data use truly began in the early 1990s during the reign of back-office reporting. Back then, the numbers were used in ways that would support business and logistical decisions made internally.
“The world is now awash in data and we can see consumers in a lot clearer way.” Max Levchin, PayPal co-founder.
The next evolution for big data came when large amounts of unstructured data were examined in big companies like Google, Paypal, and eBay. Data scientists emerged and with them the rise of data management, organization, and protocols. The next chapter of big data began when large companies realized how powerful it could be for their business and for increasing their profits.
The Statistics of Big Data
Many people in the private and business sectors do not quite comprehend how much big data has grown and how important it is to the future. The following statistics may help drive this point home:
- Within today’s digital universe, 2.7 Zettabytes exist. That’s more than 2 trillion gigabytes.
- Decoding the human genome originally took 10 years to process, it can now be done in merely 7 days
- In 2009, only a small amount of big data projects existed, keeping revenue under $100 million. By the end of 2012, 90 percent of Fortune 500 companies had big data initiatives in the works.
The Future of Big Data
Today, big data for companies has evolved into predictive and cognitive analytics. Though it may sound like something out of a sci-fi movie, the artificial intelligence (A.I.) used to gather big data and predictive modeling information is becoming a vital tool used to make important decisions in the business world. As we move closer to analytics becoming completely automated, machines may soon dictate major business moves. According to a PwC Global report done in 2017, it’s estimated that A.I. will add $15.7 trillion to the world’s economy, and local economies would have an estimated 26 percent increase in GDP stemming from A.I. use.
The science and uses of big data are still developing. This is because data analyzing tools are still in crude form, there is a lack of outstanding data scientists, and major companies such as Google have yet to figure out what data is best to analyze. However, once A.I. technologies expand and computers become even more powerful than they are today, big data and its relatives are predicted to:
- Improve healthcare
- Improve crime detection
- Increase agricultural crop yields
- Create better traffic patterns
- Create new product manufacturing opportunities
- Boost the economy
As useful as it has been and will continue to be, we must handle big data with a human touch. This means leaving room for common sense, free will, creativity, intellectual ambition, intuition, and serendipity. Innovations cannot simply come from big data. In order to make big data work for our society, we need to understand that its purpose is to inform and not to explain. It can certainly lead to misunderstandings with its inherent imperfections. We must appreciate that power of big data right alongside its limitations.