How data science helps business

What is data science?

You cannot answer this question a simple way, even though the term seems to be on people’s minds lately. Everyone is increasingly talking about data science, some are claiming to do it, others are hiring for it. But, what data science actually is?


In fact, it is a combination of knowledge from interdisciplinary fields like mathematics, business analysis, statistics, and computer science. A huge evolutionary step in these technologies paved the way for the growth of data science. As a result, it becomes a popular analysis method, even though researchers are still figuring out the exact definition of this term.

At its core, data science is all about using various automated ways to scan, analyze, and extract large amounts of information. With advanced automated analysis techniques popping up everywhere, data science is creating new fields of study, making a direct impact on areas like humanities and social studies. Data scientists gather huge amounts of information and then use advanced algorithms to identify knowledge gaps and extract the information they want.


Currently, 65% of businesses already report the positive influence of big data on their competitive potential. Noteworthy is that the influence of data science on different studying fields is expected to grow even further in order to bring innovation and change to the industries like academic research, media, and healthcare.

Cases in business

  • Data-driven decision making. Enterprises can use data science to track the reactions of users to their services and products. Analysis of consumer behavior patterns should be based on real data, not gut feelings or hypotheses. Otherwise, it would be needless to make any business decisions at all.
  • Reasonable budgeting. Data science can help you identify both positive and negative financial trends, which you can afterward use to drive the right spending habits. With the aid of data science, you can significantly cut costs on the use of low-priority services, focusing on those that fuel your business growth instead.
  • Idea validation testing. If you have fresh ideas for products or services to offer, data science can help you test them before you move on to implementation. Advanced AI and ML technologies can help you estimate the demand for certain services/products in the future, predicting future market trends, and thus making a go/no-go decision.
  • Market research. Leveraging customer data is good, but usage alone is absolutely non-effective without research and analysis. Studying the consumption habits of your target audience is crucial for making the right marketing choices. Analyzing demographics of your customers also helps you to understand, where your target market is, and how you can capitalize on it.
  • Cash logistics. Forecasting in cash management systems is a very specific use case, which may be beneficial for ATM networks worldwide. Owners of these networks need to ensure that they hit the right balance of cash across their branch and the entire ATM network. But how to know what amount of payments to expect each day, week or month? Data science can help find the right answers. Historical analysis of payment leftovers gives an opportunity to evaluate payments data from current and previous seasons. Based on that, you can draw objective, data-driven predictions for the future.

How data science helps business

To be honest, the benefits of data science brings to businesses worldwide all boil down to three things. These include nearly unlimited capabilities of business analytics, predictive analysis, and data-based decision making. Let’s take a closer look at each of these three to fully understand their potential.

Business analytics

The most important questions business analytics is expected to answer include:

  • ‘Where we are now?’
  • ‘How we got where we are now?’
  • ‘What happened to customers, product, and revenue in the past?’

Things like retention measuring, funnel analysis, and user segmentation can help businesses grab answers to the listed above and any additional questions. Result? A deeper understanding of a product and a customer with an exact vision for their past and ongoing interactions.

Predictive analytics

This type of analytics is supposed to answer the question ‘What will happen to your audience, product, and revenue in the future?’


Based on the data obtained from advanced business analysis, predictive analytics makes estimations of how much budgeting is needed to hit your marketing goals. Also, it can help you identify problem areas before they reach your business. Hence, predictive analytics can help you identify your weakest points of failure and the biggest areas of concern, as well as find areas for growth.

Data-based product

Using data science for creating data-based products is critical, as this method can help you find a place in an innovative niche and market. Products that work using different historical data are in demand, as they represent something new.

Various types of recommendation systems, AI-driven chatbots, voice recognition tools, and image recognition systems are all the buzz these days. The need for these products grows continually, so does the use of data science for creating these products.

So, what’s the benefit?

Basically, the biggest benefit of using data science for business is the increase in ROI. Different types of analysis, tailored to your specific business needs, can help you implement strategic business decisions faster than competitors.


As a result, you get a better understanding of the market, a higher return on investment, and more efficient business growth.

Over to you


If data science is done right, it will generate tremendous value for your business. By analyzing historical data and drawing predictions for the future, you can make your business decisions more strategic and workable.


Plus, getting into your audience’s behavior patterns is a sure-fire way to map out a user-need, and thus set your business on the road to success.

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