Big data is now used everywhere. AT&T has a database of 312 terabytes, the NSA use 30 million gigabytes a day and Facebook user share 30 billion pieces of content daily. There is big money and big opportunity in big data.
Huge scale tools are being created all the time to benefit our existence and to make our lives easier. However these tools can sometimes be easier to cheat than other systems. For example, data monitoring tools such as Google rankings can be potentially manipulated through so called black hat SEO in the hope that it will help a site rank highly within Google searches.
Similarly, the more data a business has access to the easier it is to find whatever results they want. In other words, when conducting large scale customer surveys it’s incredibly easy for businesses to construct the data in whatever direction is more beneficial to them using the masses of data available to them. On the other hand, having such a huge volume of data could make it more difficult for businesses who do want to portray accurate data which is made difficult to find among seemingly endless amount of big data out there.
Big data isn’t always the answer. As consumers we often prefer tailor made to mass produced. A one size fits all approach isn’t always appropriate. For example, a phone app designed to give you directions will have access to a huge amount of road layout and road information data and may suggest an alternative route that leads you down a closed road or construction site.
Big data requires a fast pace. Constant updates are needed in order to keep up. Using the example of the phone maps again, in order to tackle to issue of unreliability these apps need to be updated each second with road and traffic reports; the app ‘Waze’ allows users to update maps with road accidents, heavy traffic and other helpful information for other drivers.
Big data is big – obviously. Even some big businesses don’t have the power or capacity to handle the volumes of data being shared and used on a day to day basis. Utilising all of your data on your own server can be be problematic since if you have a large amount of data, you likely won’t have the computing power available to analyze it and having exactly that much power would require using 100% of your server capacity 100% of the time when running efficiently. However, if you store your business data on the cloud it runs entirely on offsite servers designed to handle big amounts of data and rapidly changing resource requirements, relieving your servers of the workload and giving you flexible, cost effective processing power.
“Cloud based technology is extremely flexible”
Storing your data on the cloud gives a flexible amount of processing power of which you only pay for what you use; when analysing infrequent chunks of data, you can see the obvious appeal.
A major success story being Amazon who, after introducing cloud computing within their network, realised that they were only using 10% of their service capacity most of the time saving them a huge amount of money.
So is big data a winner or a loser? There are arguments on both sides however I strongly believe that when used properly big data is most definitely a winner.
It’s the future (and the present) and ought to be embraced by big businesses. It’s a fast paced beast that we should all get a handle on before it swallows us all up.
