Use of Business Analytics in Machine Learning with Examples

Imagine heavy traffic, and you’re miffed because you need to reach somewhere urgently. Like every other person belonging to this generation, you will take help of Google Maps to check the other optional route which has less traffic congestion.

Likewise, we take help of machines everyday to make decisions in our everyday life. Of course, even Google Maps learns and improves over a period of time.

We cannot imagine our life today without these smart devices. A couple of years back, communicating with someone or using these apps would have seemed a myth or a distant dream. But machines are there everyday, everywhere, a part and parcel of our professional and personal lives. So what is this exactly? The penetration in our everyday lives of smart devices, who can think and improve their performance, has created a difference everywhere.

Of course, these machines have also created a paradigm shift in the booming sector of business analytics. In simple words, business analytics is ‘converting data into insights’. These machines have made it easier to collect data, analyze them, and even give sharper results that are crucial for businesses to grow.

Let’s take some more examples,

  1. Social Media: Every Facebook user receives feeds on a recommended book to read, gadgets to buy. All these feeds are courtesy predictions of machine learning which predicts the likings of the consumers on the basis of previous data collected.
  2. Amazon Model: You click on an email which directs you to Amazon’s products. The machine learns and collects the data on the basis of time spent on surfing and clicks made. Thus, they receive information about your preferences, and will know which products to target at you. Also, they receive insights about which content is appealing to a consumer, so that it induces him to spend more time surfing around.
  3. Face Recognition: The face recognition technology has improved over a period of time thanks to machine learning techniques that has improved the quality of output, giving perfect recognitions.

So, let’s get into the nitty-gritties of machine learning to understand what exactly it means and how exactly it can be useful.

What is Machine Learning?

According to SAS Institute:

Machine learning is a method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look. With more and more data, it will produce superior quality insights.

(Source: SAS Machine Learning )

In simple words, the machine learns itself on the basis of previous experiences and results, thereby improving its performance, without any explicit programming to do it.

So what does future entail for Business Analytics?

It is said that Machine Learning is all set to unleash the power of big data and year on year it is witnessing a lot of changes.

As per an article by Analytics Magazine

Machine learning is helping infuse bits and pieces of shattered information to create useful insights. More and more data is created through social media, automatic censors, and other sources.

Source: Analytics Magazine – Machine Learning

How Machine Learning is helping in Business Analytics?

Traditional Business Accounting requires a degree of human intervention, which will be discarded by machine learning, since it continuously updates its learning, without being explicitly programmed to do so.

With self-driving cars, and other smart devices, which assist humans, and even take over it completely, machine learning is certainly the next hot piece of cake in the market. All eyes are set on it on how it will impact business analytics.

Realizing the potential of business analytics, many companies are seeking out to harness business analytics tools to help achieve a competitive edge. Machine learning is the cherry on the cake, which will help scan structured and unstructured data; and extract appropriate data to take correct decisions.