Big data is massively valuable.

According to IBM, .5 quintillion bytes of data are created every day. And, in a study done by Forbes Magazine, "70% of IT decision-makers consider their organization’s ability to exploit value from big data as critical to their future success." Big data is indeed big--massive, actually--because, in the information age, the secret to more money is in the data. Consider, for instance, that the ride-sharing app Uber is valued at $42 billion not because it's a realiable taxi service, but because it's become adept at gathering information from its customers that will most likely become more valuable than the customers themselves.

Uber's side business is big data.

 

The data-driven marketing economy (DDME) added $156 billion in revenue to the U.S. economy and fueled more than 675,000 jobs in 2012 alone. Over 70% of the value of the DDME—$110 billion in revenue and 478,000 jobs—depends on the ability of firms to exchange data across the DDME. Big data analytics companies revenues are soaring and investors are pouring money into this field.

The more the data a business has access to, the higher the probability of its success. Big data helps trim operating costs drives focus on better management and customer growth. A simple example of this is when sellers on Amazon or eBay study data to find out which items are in top demand. Most beginners start their online businesses by referring to Amazon’s top-selling list because it's better to understand the market before sourcing the inventory. Data can be as detailed as the number of items sold, how long the item was trending, what time of the day it was sold the most, what the average seller profits were and so on.

The Fire Stick is #2 on Amazon's top-sellers list. No reason why.

Any business--from restaurants to software companies--requires data to succeed. In today’s connected world, individuals an organizations are dead unless they're online. These digital footprints convert to data, which model the behavior and desires of customers. Wanting to sell your new dev kit to customers? You'll need data to do it.

Big data is the backbone of automation in industries like health science and space tech, and it helps drive the Internet of Things (IoT). Autonomous vehicles can be more reliable than human beings, but this is only the case if that machine is powered with enough data. Tesla Motors, which just rolled out its first semi-autonomous feature in the Model S, has several sensors equipped throughout the car’s body that collect data for safe driving from its surroundings. The car analyzes this data and learns the tricks of smoother driving in the uture. When one car learns something, this data is communicated to the entire Tesla fleet, so all cars learns the same thing.

So what about Google, the mother of all data? There's a reason it's one of the most precious companies in the world: it knows the most. Google analyzes the data from topics people are searching for, which helps the Google search algorithm becomes progressively more intelligent and increasingly faster. The reason Yahoo! and Bing have aren't as good as Google isn't because Yahoo or Microsoft can't afford to hire better engineers: it's because users are so dependent on Google that it strengthens the database to make it faster and better with every search. 

 

This all means that engineers have access to companies that can provide whatever data analysis they need. For instance, Terapeak can help engineers see which items are hot on eBay to gauge consumer interest. For startups, Kissmetrics is a good option: the company can tell you exactly which customers are being reached and what roadblocks need to be addressed. A Utah-based company called Domo delivers custoized IoT solutions. EEs would do well to keep their eye on how big data can solve their dilemmas: after all, data is the ultimate force powering technological breakthroughs.

 

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