How big data has become accessible to everyone
It’s been the narrative of technology since the wheel was invented. Something is new, exciting … and expensive. Then we find a way to mass produce it (or something similar). Processes get better, and equipment gets cheaper. Consumers save big. Then something new comes out.
When big data first rose to market prominence, critics were quick to pounce on the same tired old complaints — it’s too expensive, too insecure, too volatile. We don’t know if it will work. We don’t know if it will make any difference. It’s just too complicated. But data scientists, like their forebears in all realms of discovery and research, turned a deaf ear to the naysayers. They kept working, they kept learning … and they kept getting better.
Today, the marketplace is enjoying the fruits of the established connection between increased data (thanks mobile!), better math, and increasingly cost-effective data storage options. Data scientists can capture more information, understand it better (and easier) and they can store more information — and hold onto it longer — than they could before. These innovations have led to incremental increases in the benefits enjoyed and diverse results gathered from big data.
Now it’s not only the data scientists who are paying close attention to the progress of big data analytics. Business analysts, prognosticators and serial entrepreneurs are digging into the data and finding their own personal pots of gold at the end of a very long and complex data rainbow.
Advanced analytics mean that businesses can better understand their customers and prospects. Instead of carpet-bombing advertising campaigns, they can launch “smart bomb” adverts and build websites that customize themselves for every new visitor.
Internally, businesses are enjoying better and smoother human resources operations. They are finding better fits for positions early in the hiring process. They are tracking how workflow and environment impact their profitability and acting accordingly.
History tells us technology will continue to be refined, making data analysis — and its myriad benefits — better, smarter, and faster. Thinking machines are already moving beyond gathering and collating data to crunching and making connections. Not too long ago, IBM’s Watson was a sideshow anomaly competing on Jeopardy. Today, thinking machines are turning data gathering into a growth industry.
What will tomorrow bring? We can’t say for sure, but we do know big data will be in the driver’s seat.
