Why is data science important? It is a question that a lot of people ask me, especially if they are not familiar with the industry. Data science, data scientists, and similar buzzwords have been circulating for quite a while now, but very few of us know how important this field is. Data has become a new energy source because we live in an era controlled and influenced by data. As a result, Data science came into the mix because of this ever-growing reliance on data.
What is data science?
Data science is a study to extract valuable information, knowledge, and insight from a huge amount of raw data. Data scientists use scientific approaches, techniques, procedures, frameworks, and algorithms to churn enormous data to find out facts, trends, and statistical evidence to equip leaders to make informed decisions.
Why is data science important?
Data science is making, if it hasn’t already, its way into almost every aspect of life. Why is it so? Why has data science become indispensable? The answer is simple. It’s the usefulness of data, and data science is making it more useful and more insightful.
You may say that we have always had data, and we have always derived value and insights from it. But, there is a reason why data scientists are amongst the top paid workers out there right now. It shows how valuable They are to a company.
A data scientist works quickly.
The reason why they are important is that they are skillful in multiple mathematical and business domains. They vary from maths, statistics, visualization, programming, public speaking, etc. But most importantly, they can derive insights faster than ever.
Think about it a second, the previous decade, how long would it take to process, analyze, and infer a dataset with over 15 million rows. My guess, several weeks if the dataset is cleaned, more if it is raw. For the same clean dataset, it will take nowadays for a good data scientist a few hours for a basic Exploratory Data Analysis (EDA).
A data scientist will provide you with tons of insights.
A good data scientist knows how to manipulate the data in a way that you didn’t even think was possible. They can collect, wrangle, transform, and use different mathematical algorithms on the dataset. Consequently, they can understand what is going on and present it in an understandable way to the shareholder that needs the information. Hence, they can transform information, into insights that lead to better decision making.
A data scientist will be able to improve your services through automation.
You can see a lot of ways data science improves services. Just follow me on Twitter. I share so many innovations in the industry that are helping companies save money.
For example, talking from my own experience, e-commerce makeup companies tend to lose a lot of money because their customers tend to make mistakes when selecting the proper shades for their skin tone. I wrote an app that would automatically detect the skin tone from a picture or the webcam. It allowed the website to give the correct recommendation of products according to the customer’s skin tone. As a result, the company experienced a 45% decrease in the rate of the returned product. It followed a 28% increase in the product rating over the next 2 months.
There are so many ways that data scientists help improves services that I will dedicate a whole new article to it. In a nutshell, it involves classification, prediction, clustering, recommendation, ranking, and many more
Let’s see the importance of data science applied in a few industries. If you have found this information useful to you, please subscribe.
1. Why is data science important for businesses?
Business leaders and executives always try to make the right and careful decision. They need data to base their decisions on facts and figures. The use of data science can oblige and lead them to data-driven decisions. It helps businesses beyond any stretch of our imagination. For instance, it helps businesses hit the right audience. If used correctly, you can not only convert leads into customers but maximize your chances to turn sporadic customers into loyal ones. It can play a key role in almost all the operations of a business. Those applications range from R&D to production/manufacturing, and marketing.
2.Why is data science important in healthcare?
Data science is also playing a crucial role in healthcare. It is assisting in preventing the spread of diseases, especially in epidemiology. Additionally, Data science is helping medical officials in detecting chronic diseases at an early stage. It is also extremely helpful in monitoring patients’ health. For example, data collected through Internet of Things (IoT) devices is analyzed through machine learning techniques. In short, data science is not only leading us to better healthcare but also optimized economic spending on healthcare.
3.Why is data science important in engineering?
Data science is playing and can play a pivotal role in different fields of engineering. When we look into engineering, data is everywhere. Consequently, Data scientists and Big Data experts emphasize incorporating it in all major disciplines of engineering. The applications in engineering are endless and will do unimaginable good. For instance, it is almost impossible for a chemical engineer to predict the biological response of a new molecule analytically and handle 1776 molecular descriptors details. But, data science has made it possible with precision and perfection.
4. Why is data science important for social wellbeing?
Artificial intelligence and technologies have progressed and developed over the past few years. Data is available and also has become more prolific. Isn’t it time to use advancements in technology and data fields for social good? Education, criminal justice, public safety, infrastructure, healthcare, environment, etc. can capitalize on data science and can be extremely good for society. You can visit the website of Carnegie Mellon University’s The Center of Data Science and Public Policy and find some examples of how impactful data science was in social sciences and public policy.
There you have it. If I have missed something, do let me know what do you think about why data science is important? (Or not important).
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