Why Data Science?

• Traditionally, the data that we had was mostly structured and small in size, which could be analyzed by using simple BI tools. Unlike data in the traditional systems which were mostly structured, today most of the data is unstructured or semi-structured. Let’s have a look at the data trends in the image given below which shows that by 2020, more than 80 % of the data will be unstructured.
  
  This data is generated from different sources like financial logs, text files, multimedia forms, sensors, and instruments. Simple BI tools are not capable of processing this huge volume and variety of data. This is why we need more complex and advanced analytical tools and algorithms for processing, analyzing and drawing meaningful insights out of it.

This is not the only reason why Data Science has become so popular. Let’s dig deeper and see how Data Science is being used in various domains.

• How about if you could understand the precise requirements of your customers from the existing data like the customer’s past browsing history, purchase history, age and income. No doubt you had all this data earlier too, but now with the vast amount and variety of data, you can train models more effectively and recommend the product to your customers with more precision. Wouldn’t it be amazing as it will bring more business to your organization?

• Let’s take a different scenario to understand the role of Data Science in decision making. How about if your car had the intelligence to drive you home? Self-driving cars collect live data from sensors, including radars, cameras, and lasers to create a map of its surroundings. Based on this data, it takes decisions like when to speed up, when to speed down, when to overtake, where to take a turn – making use of advanced machine learning algorithms.
• Let’s see how Data Science can be used in predictive analytics. Let’s take weather forecasting as an example. Data from ships, aircraft, radars, satellites can be collected and analyzed to build models. These models will not only forecast the weather but also help in predicting the occurrence of any natural calamities. It will help you to take appropriate measures beforehand and save many precious lives.

Let’s have a look at the below infographic to see all the domains where Data Science is creating its impression.

Who is a Data Scientist?

There are several definitions available on Data Scientists. In simple words, a Data Scientist is one who practices the art of Data Science. The term “Data Scientist” has been coined after considering the fact that a Data Scientist draws a lot of information from the scientific fields and applications whether it is statistics or mathematics.

What does a Data Scientist do?

Data scientists are those who crack complex data problems with their strong expertise in certain scientific disciplines. They work with several elements related to mathematics, statistics, computer science, etc (though they may not be experts in all these fields). They use the latest technologies to find solutions and reach conclusions that are crucial for an organization’s growth and development. Data Scientists present the data in a much more useful form than the raw data available to them from structured and unstructured forms.