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SmartData Collective > Analytics > Predictive Analytics > How Predictive Analytics Will Affect Big Data’s Future
Predictive Analytics

How Predictive Analytics Will Affect Big Data’s Future

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briggpatten
5 Min Read
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Predictive analytics is one of the biggest trends in business today. There are many companies investing time and money into this area of their business. However, there is also a lot of new technology coming out in this sector of technology. Predictive analytics takes big data one step further. Instead of just looking at the data, predictive analytics makes an informed prediction off of the data presented. This is a huge next step for any company. However, there are a couple of things to keep in mind when it comes to using predictive analytics.

Predictive analytics is one of the biggest trends in business today. There are many companies investing time and money into this area of their business. However, there is also a lot of new technology coming out in this sector of technology. Predictive analytics takes big data one step further. Instead of just looking at the data, predictive analytics makes an informed prediction off of the data presented. This is a huge next step for any company. However, there are a couple of things to keep in mind when it comes to using predictive analytics. Here are several ways this will affect big data’s future.

Using Predictive Analytics

There are many different ways a company can use predictive analytics in their business today. Perhaps the best example would be before a product launch. In years past, a company would simply have to hope that their product would sell when it launched. However, with the technology that is available today a company can predict with some accuracy how a product will sell. This is a huge turning point because companies can now forecast events so far down the road. This has a much larger effect in growing industries like online education. An elearning company that wants to launch a couple of classes online can now predict how many people will sign up and plan their launch around the number of new users. This opens up so many possibilities for companies in the future for planning purposes.

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What is Big Data?

One of the biggest increases in technology over the past couple of years is the fact that companies have more access to data than ever before. It is now much easier to store and manipulate big chunks of data to increase ROI. Over time, a retail company can collect data on millions or even billions of customers. Looking at one customer may not be helpful, but when a company looks at a huge data set there are trends that are easy to see. One of the most famous example of this involved a retailer who automatically sent out pregnancy coupons to people who were pregnant. The problem was this was a teenage girl whose father did not know about the pregnancy. This is just one example of how big data can predict outcomes based on a set of data.

Limits of Big Data

Although all of this information is great, there are some limits to big data. Predictive analytics are going to be as accurate as the data that is used. The technology in the field is nowhere close to artificial intelligence yet. This means that if flawed data goes into the system, a flawed decision is going to come out the other side. Companies need to make sure that all of the inputs along the way are as accurate as possible for the best outcomes here. Over the long term, the extra effort that is put into making good data decisions will go a long way in helping a company.

There are many different ways that predictive analytics can help a company make decisions. There are so many uses of technology in this field that entire companies have been changed for the better. Big data is great for making informed decisions. However, predictive analytics takes big data one step further in actually projecting out what will happen. As a warning, these analytics are only as good as the data that is put in. If there is an inaccuracy somewhere along the way, the decision that comes out is going to be flawed as well.

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