How Data Science Can Resolve Business Problems

Data Science


Data science is the field of study that uses scientific principles and advanced analytic techniques to extract valuable insights from data. This information is then used for strategic planning, business decision-making, and other purposes. Log on to any connection such as Cox Bundles and you will find ample material on how data science can help companies improve their business. 

Following are some of the key ways data science helps businesses. 

#1. Customer Insights

Through customer data, you can get details such as their demographics, habits, preferences, and much more. Such data is collected through sources including social media, email, website, and more. When you have a lot of data, it can be hard to make sense of it. This is where data science comes in.

Firstly you need to verify that the data sources are authentic. Then you start the process of data wrangling. This involves matching a customer’s credit card information with their email address, purchase identifications, and social media profiles. By doing so, you combine the data to identify behavior patterns and draw conclusions. 

This gives you a better understanding of customer needs. You can then devise your marketing strategies accordingly and ensure that your product provides a viable solution to the customer’s problem. Besides, understanding customer data can also help you provide a personalized customer experience and discover other ways to improve your website. 

#2. Improve Security

As companies become increasingly data-centric, the need for the ethical treatment of data becomes more important. Data science can help boost your business security by protecting confidential or sensitive information. 

Banks use complex machine-learning algorithms to detect fraudulent activity. The detection is based on the deviation from a user’s usually financial transactions/activities. These algorithms are more accurate in their detection than human beings. And that’s mainly because of the volume of data they deal with every day. 

You can use algorithms to protect data via encryption. However, you need to be familiar with data privacy laws and practices so that the company does not end up sharing or misusing sensitive information (even by mistake). The right combination of human judgment and algorithms is what helps a business maintain ethical use of data and a high level of security. 

#3. Managing Internet Finances

Finance professionals use data science to analyze financial trends, create reports as well as generate forecasts. Data regarding a company’s assets, debts, and cash flows is gathered constantly. Financial analysts can use this information to detect trends in financial decline or growth. 

For instance, if you are an analyst responsible to forecast revenue, you can derive the results by using predictive analysis. Similarly, you can employ risk management analysis to calculate whether or not certain business decisions are worth taking. Such financial analysis can give meaningful insights and facilitate the stakeholders to make better business decisions. 

#4. Crisis Problem-Solving

Countless businesses suffer failures owing to unidentified problems within their systems/operations. When businesses are unable to recognize where a problem lies, data scientists can help them locate its source/cause. A common method to do is factor analysis. It is a kind of statistical analysis in which scientists break up a process into the parts that constitute it. This lets them determine which part of a process is causing or contributing to the issue. 

#5. Streamline the Manufacturing Process

 Businesses can also make use of data science to look for loopholes in the manufacturing processes. The machines collect data from production processes in high volumes. When the amount of data gathered is too high for an individual to analyze manually, you can make an algorithm to interpret and sort it accurately. 

Take the example of Oden Technologies. The company came up with a machine learning tool by the name of Golden Run. It collects the manufacturing data, identifies the highest efficiency, and gives recommendations to replicate the same level of efficiency. As the tool collects more data, it becomes capable of providing better suggestions. Therefore, you can rely on data science to increase efficiency, cut costs as well as produce goods in large quantities.

#6. Data Value Exploration

Data exploration projects are usually for those companies that are new to data science. Many such companies have huge chunks of data and have no idea whether or not it is of any use. In such cases, the data scientist needs to explore the data to identify its potential. This is called an exploratory analysis. It requires a lot of work on the part of the scientist as they have to arrange data into an organized dataset. This lets them explore opportunities that went unrecognized before.

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