What is Data Science?

This is a science where we extract information and knowledge from structured and unstructured data sets through algorithms, scientific processes and mathematical systems. In this process we give meaning to simple data. After that data goes through these processes, we can make predictions, assumptions and decisions. So this has become a huge advanced and compulsory field because of the internet since we can get any kind of data through the internet but not much of meaning or patterns to them.

History of Data Science

Even though the term Data Science came to light very recently, this term goes back to the early 1970s. The term data science coined in 2008 and it’s credited to mathematician William S. who is considered the father of data science. Yet records show that the first data scientist in the world was Tobias Mayer who was born in 1723. He explained the motion of the moon by collecting data using spherical motion trigonometry and compiled them to make sense out of them.

In today’s world, data science has many sub fields and it’s connected to so much like deep learning, finance, bioinformatics, health, information economy, social media analytics and network analytics, business analytics and logistics and many more. So this is a field that has a rapid growth in popularity and importance since it’s connected to almost everything through the internet.

Advantages of Data Science

There are countless advantages of this field. Basically companies can gather data and understand why their product makes so much profit or loss, why it sells on some continents and not on others, to whom the product would sell easily and why etc. So basically, for any type of organization, data science will become a compulsory if wants to have rapid growth and make genuine profits.

Also, through this, we can customize personal experience. This is because the marketing and sales teams can understand the audience or the user on a very basic level through data science. Through this, they can create the best experience a customer can have.

As mentioned above, companies and even governments can make better decisions using data science in any kind of situations from food distribution to global pandemics. On an organizational level, this can help recruited the best people for the team and identify opportunities. Also this will help make better goals and achieve them efficiently for anyone who uses data science as a tool.

What does a data scientist do?

As mentioned above, in modern world, the role of a data scientist has become essential for an organization. But what does this role brings to the table? What is the use of this role? It’s simple.

Data Scientist helps make major decisions in an organization or in a government. He or she does this by analyzing data with the help of computer science, mathematics, analytics, statistics skills and giving meaning to those said data sets. So with the help of a data scientist, an organization can make bigger and better more secured decisions based on facts for the future rather than assumptions.

Business Intelligence VS Data Science

Even though these 2 terms have alike processes, the definitions are different. In business intelligence, we process data to give meaning to the present and the past (using present and past data). On the other hand, in data science, we use analytics to give meaning to data to make future decisions or predict the future. So in general, BI is used to identify the mistakes made in the past or make sense on what happened in the past and what’s happening in the present. Data science is used to make decisions in the future and to understand the future.

How to be a Data Scientist?

This is not an easy task since it requires a lot of skills and knowledge. But if you really want to be a data scientist, then the first thing you must get is a bachelor’s degree in information technology, computer science, physics, math or any related field. The next step is you have to get a master’s degree on data or any related subject. Then you can become a data scientist by getting experience on the field you want to work like healthcare, business, physics etc.

But it’s not easy as it sounds. You must require a lot of skills to become a better data scientist. You must be really good at statistics, data visualization and big data procession frameworks. Also you must be really good at least at one computer language like python or java. Also you must be familiar with machine learning and related algorithms, deep learning (advanced machine learning) and data exploration.

So it will take time for you to be good at these things since it require a lot of hard work to become good at above mentioned skills. But the outcome will also be very good. The average salary for a data scientist in USA is $100,600 for annum. But if you become an experienced data scientist with a managerial role, then you can earn up to $250,000 per annum.