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UNDERSTANDING THE PROBLEM We live in a world which has literally evolved to be a place where every second person has the option to play God (in a miniature role) in terms of predicting future events. Future as in not really telling what is going to happen to a person or to the world, but we as humans definitely have the power at our disposal to predict normal things to higher levels of accuracies- things such as telling whether a business as per its current practices is going to sustain for long or not, detecting some sort of suspicious activity, etc. All these things fall under the category of what we call predictive analysis, which basically helps businesses and people to get a vague idea of the near future and take some steps and implement measures preemptively to make sure that the damage sustained from the resulting events is minimal. All of this is extremely easy to hear and listen and extremely tough to actually implement. There is a ton of computation power as well as brainstorming of a bunch of human minds to actually pull it through. It is a complex capability to have that has its own set of challenges that we shall take a look at. CORE CHALLENGES 1. ROI The biggest challenge with data analytics is actually getting the right amount of returns on the entire investment on the project all burning down to the infrastructure costs, human labor, maintenance costs, developing costs and whatnot. A lot of businesses just out of trend, decide to implement a data analytics project on their premises without understanding much about it which is why it is not at all uncommon to see organizations that undertake a data analytics project and are completely dissatisfied with the impact of its results and findings. It is imperative that one first evaluate whether or not analytics is what their business needs at the moment, for in the end, it is just a waste of both time and money for you as well as for the analysts who wasted precious efforts all for nothing. 2. Sourcing the right talent It is not at all a well-hidden fact that the balance of the demand and supply of talented people in the field of data science is not at all in equilibrium with the supply nowhere even matching the demands. Finding a data analyst is not at all a tough job, but finding one with the right set of talents and skill set has proven to be extremely difficult which is why top companies and organizations are willing to splash ridiculous amounts of money just to land themselves a master of the art of analytics. 3. Funding Even after evaluating all sorts of needs and deciding that an analytics project would be in the best interest of a business, securing funds and budget for the same proves to be a bottleneck for many. For larger organizations, the board is never onboard while for smaller organizations, the expenditure seems to be too much for them and they just decide to pass upon it not realizing that it is an investment that is going to reap numerous benefits in the long run. RESOURCE BOX Despite its bunch load of challenges, data analytics sure is a field that garners the interest of a lot of people and rightly so, for it allows one to think way outside the box and do things that actually change the world for good (even if on the smallest of scales) and so if you are one of those people that is attracted by the fancy work of data analytics, choose the best data analytics course for yourself today.

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