Decoding Data Science in Business Models

As the businesses are now moving towards digitization, understanding the application of data science would improve customer satisfaction and help in applying data science in modern-day practices.

Around the world, businesses are now shifting to digitization. With the help of analytics and Artificial intelligence, businesses are now paving its path towards improving customer satisfaction. The demand for data science is an all-time high. Infact, Data Scientist was ranked amongst the top Required Jobs by LinkedIn for the year 2020.

However, despite its massive demand and progressive advantages, understanding data science and acknowledging its challenges has become imperative for any business model to work.

What is Data Science?

Data Science is the process of using algorithms, processes, and methods to abstract knowledge and insight from structured and unstructured data. By applying the tools of machine learning and using analytics, the organizations can predict, and enhance optimizations, operations, and decision-making capability.

How does Data Science Work?

Like any business model demands, better prediction, and optimization, Data science engages in the gathering of data from relevant sources, cleaning it and putting it in formats that Machine learning understands. After this, with the help of statistical methods and using algorithms, the patterns and trends in Data Science are established and models are programmed to predict and forecast a solution.

Importance of Data Science

In this fast pacing world, when the competition amongst organizations is rendering them to be innovative and resilient, data science furnishes organizations to be agile. With the help of intelligence and data science, businesses can extract greater value from the available data.

Data science has a broader role in the current business model as it helps businesses to strategize for possible solutions. With the help of automating data, the more interesting and innovative aspects of the field are addressed by experts. It is estimated that by the year 2025, 50% of data science will be automated by AI.

A report by IBM suggests that almost 85% of data scientists spend their time cleaning, shaping, and moving data from place to place that leaves only a small fraction of the data scientists to identify patterns and trends, to build models, to predict and forecast and interpret results.

With the help of AutoAI, the latest advancement of Artificial Intelligence, the data preparation and modeling stages of data science can be automated.

Opportunities in Data Science in the Modern World

The application of data science is vast. That's why more and more companies are indulging to apply data science for reaping lucrative rewards.

With the help of data science, organizations can identify the pattern of customers' behavior, for delivering the desired products. Data science empowers the organization to design the product and services according to the convenience and choices of customers.

With the help of observing customer feedback, organizations are presented with an opportunity to improve their marketing strategy. With the help of making improved promotions, the chances of customers getting attracted to a particular product are high.

Data Science also presents the opportunity to strategize and re-strategize, by identifying the loophole that's disrupting the flow of business. With the plethora of data available, data science segregates structured and unstructured data, thus reducing the chances of fraud.

Identifying the objectives and necessity of those objectives, a roadmap to those objectives, and determining the priority points are some of the opportunities presented by Data Science.

Data science also enables organizations with new opportunities. For example, with the help of data science in an hospital setup, the pharmaceutical manufacturers can identify the preferred medicines given by oncologists to their patients and the patients response to those medicines.