artificial intelligence

The rewards for knowing the future in advance are great, but they frequently remain unclaimed due to the flawed nature of human predictions. Artificial intelligence, however, is having significantly more success.

This is a rapidly evolving industry, however, and advances in artificial intelligence (AI) could soon see us base our future projections on reliable statistical models rather than our familiar-but-flawed intuition.

What is predictive analytics?

Predictive analytics is a form of data mining that employs machine learning and statistical modeling to predict future states of affairs, based on historical data. For example, Google Trends used predictive analytics significantly over the last 5 years.

We can look at this line and predict that it will continue to grow. But that is really just based on the recent historical trend or the fact that we have heard a lot of buzz about the topic in the industry. It would take a lot more investigation for us to assert with any real certainty where the line will go next. Prediction is not easy it takes a lot investigation to assert with any real certainty. Scientists predict that billions of dollars will spend on big data technology by 2020. Therefore, the best way to return this investment would be to use that data to anticipate future demand trends. Many analytics professionals engage with this field every day to calculate figures.

What is relatively new is the application of artificial intelligence to plug gaps in our skill set and extend what is possible with predictive analytics.

This combination has led to more sophisticated statistical models that spot patterns in past consumer behaviors and use these to map out likely future actions.

How can businesses integrate predictive analytics?

There are four elements that organizations need to capitalize on artificial intelligence and predictive analytics:

1.    The right questions

Everything starts with a good question and then providing machine learning algorithms to answer it. Starting with a business challenge is a good idea.

2.    The right data

     Now we need access to structured data to analyze and find the best answer.

3.    The right technology

We need technological capabilities to capture, store, and make sense of data. There are so many predictive analytics tools but every business needs a professional team to identify the best suitable solution

4.    The right people

The most important option is to have right people. Right people to find questions, find data and to use the best technology. For all of the talk of AI replacing people, it has only really sharpened the focus on getting the right people to make the most of the new opportunities it creates.

Source :

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