You know how you are browsing through your friend’s profile on Facebook and all of a sudden an ad crops up with the image of a smart phone that you have been dying for since days? Or how a similar thing happens while you are watching your favourite videos on YouTube? Believe it or not, Big Boss, sorry, big data is what’s behind all this. Simply put, big data is what it’s called – big data. One can argue over the context in which the term ‘big’ is used here. Is it used to refer to large amounts of data or does it imply that the importance or relevance of any amount of data is huge? The answer is both. The government has details like name, age, gender and address of every citizen. Considering the sheer amount of data that the government has, this can be said to be ‘big data’. Similarly, a space programme has big data regarding the contents of the universe. An organisation like Apple or Google has big data about how consumers use their services to access the internet. Big data is present in every sphere of our life. Here are a few things that will help you understand big data better –
1. Big data is useful for everyone – Whether you are a multi-national corporation sifting through the big data in order to gauge consumer tastes and preferences or an intelligence agency looking to find terror angles through a huge bunch of emails, big data is omnipresent. Even a small business has a lot of data which can prove to be very useful not only for itself but also for other companies that either procure or supply materials from/to it. There are online companies that use this data in order to analyze their target audiences, for instance, you have betting companies that are interested in learning about the behaviour of their potential clients. They analyze online players on how they bet with comeon, what game interests them the most and so on.
Scientists use big data to analyze how certain diseases are affecting a particular geographical location and how they can the information from that data to restrict the spread of such diseases.
2. People with big data skills are scarce – Even as the world is realizing the existence and immense usefulness of big data, people who can actually help you interpret that big data are not found in huge numbers. One reason behind this is that there aren’t enough educational programmes designed around the skills that make a data scientist. So there is a vicious circle where since there is not much knowledge about the importance of big data, there isn’t much demand, and hence not much educational support. But if studies are to be believed, then big data is going to be even bigger in the future and people who can master the required skills would be making a lot of money. So don’t listen to those who ridicule you when you say you wanna become a data scientist. Chances are everyone will be flocking to this field in a couple of years.
3. Big data is considered a resource – Considering its relevance, big data is considered a resource which needs to be dealt with carefully and efficiently. Earlier, corporations had no idea about the fact that the data which they had gathered for years could be used to their advantage. Ever since the concept of big data has gained currency, however, they are becoming increasingly aware about various ways in which they can gather more data, be it from proprietary sources like their business partners in the supply chain or from public sources like population demographics released by the local governing body or statistics published by the economic department. Once you the data, you can look for patterns and try and get some mileage out of it.
4. Technology can make a lot of difference – The high costs of big data are often talked about. Many go on to say that a small business neither needs big data nor can it afford it. Wrong, on both counts. Even though the name may convey otherwise, big data can work wonders for a small business. It depends on the kind of business. Unless it is a business where data doesn’t make a difference, big data is always a handy tool to invest in. coming to the affordability aspect, a small business can cut down on big data costs in two ways. Either they can use available tools like Hadoop, InsightSquared and Canopy Labs or they can choose to invest in a data scientist. However, there are divergent views on whether a small business needs to go so far as to hire a data scientist. While some feel it is good in the long run to have an in-house data expert who understands your business and can help you to use the information others argue that this task can easily be done by freelancers and contractors. A few bucks here and there, but no one suggests you to ignore big data. When it comes to big data, ignorance is no bliss.