Sure, world is crying out loud that big-data’s biggest problem will be resources. Demand has skyrocketed and everyone in the world is going into tailspin in meeting that demands. Companies are going frantic and overspending to hire data scientists to secure themselves from any upcoming shortfall. This is nothing but a sign that world needs our robot algorithm friends to pacify some demand and increase credibility to new paradigms. Who could forget Steve Balmer’s famous quote comparing Big Data as a Machine Learning problem. For starters, consider following 5 pointers why Machine Learning will have the last laugh when it comes to handling big-data first hand.
Too much data and too few people: Firstly, this is a no surprise that machine learning algorithms will work at the pace not matching their counter scientist friends. If trained properly, machine could easily pacify majority of data preparation and analysis demand in data analytics world. Another cool thing about machine learning is that once code is prepped and machine is programmed, you could use it multiple times and multiple places and see the magic happen. The trick is to not overkill first but to use it for overhead tasks first and keep making it more and more sophisticated, so that it will start doing all the heavy lifting and pacifying the resource demand as a result. Hence, machine learning single handedly can reduce big-data resource crunch and make the resource distribution relevant and appropriately. – See more at: http://v1shal.com/content/the-silent-rockstar-of-bigdata-machine-learning/?utm_source=rss&utm_medium=rss&utm_campaign=the-silent-rockstar-of-bigdata-machine-learning#sthash.xKJJhKQD.dpuf