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How Data Science Solves Real Business Problems?

Abzooba Admin

– Abzooba Solution Team

The field of data science is gaining momentum in the last few years. But what is data science? To a person from a non-technical background, data science can be explained as a field that takes the help of various algorithms and scientific methods to generate solutions for a problem using a huge amount of data about the given problem. It can be used to study patterns and can be said to be a combination of statistics and data analysis. Data science is “problem-solving with the help of analytics”.

What is the role of data science in the business field?

The very basic use of data science is to answer questions like “How to increase sales”. I know, increasing sales depends on multiple factors like the type of product, pricing, marketing strategy, the targeted audience, etc.; but, one thing which is of extreme importance is data. Statistics regarding business problems are used in Data science to generate effective solution pathways.

When an organization comes up with a question like “how to increase sales”, it’s the role of a data scientist to hunt for data regarding each aspect of that particular business and distribute the problem in multiple manageable parts to focus on each part effectively.

How is data science being used to solve business problems? 

It helps in modifying already present system mechanisms.

It’s the responsibility of the data science team of an organization to create a new mechanism that can bypass problems existing in the system.

For example, before the rise of data science, it was challenging to predict consumer demand patterns but now with the help of effective tools in the data science field, consumer demand predictions can be easily made. It helps the organization in preparing for the upcoming surge or dip in demands.

Data science can create entirely new mechanisms:

Data science can help create an entirely new workflow to bypass a specific problem. For example, financial firms are now using data science to predict and keep an eye on compliance gaps which may generate in the time being.

Also, chatbots use machine learning for better efficiency, instead of keeping a fleet of customer service agents who will personally guide users through the range of products. Firms are now using chatbots that can recommend products or services utilizing & compiling data about the search history, order history, and basic data about the user itself. It is the effective use of data science to completely bypass the problem of maintaining a team of human agents 24*7.

Data Science helps in Financial analysis:

When an organization faced unexpected, unknown financial problems, data scientists must look out for the sources with the help of effective factor analysis to understand the problem and predict solutions.

To conclude, it can be said that data science stands on three pillars of sector expertise, programming, and statistics (mathematics). These three pillars are required to extract data from multiple sources to study the problem and understand it enough to predict solutions using algorithms. Not only data science is helping us to generate solutions for organizations but is also helping to understand the complex business model with the help of algorithms. The field is yet to mature, and hopefully, it will grow big in the coming years.


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