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Everyone has been hearing enough about big data these days, so much to consume all the space on social media, articles, blogs (including this one) and to keep technical writers engaged. So here are some thoughts to justify all the hype.
What exactly does Big Data mean? Well, there’s no definition of big data in terms of the number of bytes but simply that the amount of information that anyone would like to process gets so huge that their standard DBMS gives up. It’s not just the information, but even insights that could be gathered from such humongous amount of data which gets too complex to be done by a legacy system. So to all those giants who are stressing out a little bit these days; all credit to big data!
Our copyright statement says “Big Data = More information = Bigger opportunities”. The rocketing increase in the amounts of data across verticals might seem to have left organizations flabbergasted, but it has indeed opened new doors for businesses to come in. There are multiple players offering Big Data analytics, Data mining and people like us who do large-scale data crawl and extraction. On the flip side, the more information we help our clients gather, more scope for business they have. But the meat of the situation is that benefits are more overwhelming for our clients than the data is for us. Firstly, the number of servers cannot linearly increase with the amount of data. And it’s just onus to maintain too many servers and distributed systems for small things. Secondly, smaller players in e-commerce or market research would not like to invest heavily in tech as the costs are not within budget thus leading them to latch on to big data solution providers. Lastly, there’s still scarcity in terms of technical expertise with big data systems thereby sourcing some bread and lots of butter to tech-savvy folks who get their feet wet with big data.
Not to forget challenges that come along though when dealing with such mind-boggling problems- there are always questions on Data API availability and associated downtime since call of the hour is real-time data (near real-time is history). Data consistency models take lots of effort and security issues remain. State-of-the art is changing however, and nevertheless the net benefits that get computed are always more than these constants that apply. And guess what? One technology always leads to another, and this philosophy is in a pure state of acceleration today given the number of leverages to our benefit.