Why do we need Data Science

The data we have today is largely unstructured and too small to be analyzed using simple BI tools. Unlike in the past where most of the data in the system was structured data, now most of the data is unstructured and semi-structured. Let's take a look at the data trends in the image given below which shows that in 2020, more than 80% of the data will be unstructured.




This data is generated from various sources such as financial logs, text files, multimedia forms, sensors, and instruments. Simple BI tools cannot process large volumes and various data. This is why we need more complex and sophisticated analytic tools and algorithms to cultivate, analyze and draw meaningful insights from it.




This is not the only reason why data science has become so popular. Let's dig a little deeper and see how science is used in different fields of data.

• A company definitely wants to give products that are suitable for its customers, what if you can make a prediction that determines which products are suitable for these customers based on existing data such as past search history, purchase history, age, and salary. of course this will increase sales at the company.
• in the future, the entire car will be able to drive itself, so how can the car recognize its surroundings? The self-driving car will collect live data from sensors, including radar, cameras and lasers to create a map of its surroundings. Based on this data, he's made decisions like when to accelerate, when to overtake, and stop using advanced machine learning algorithms
• Let's take a look at how science data can be used in predictive analysis. Let's take as an example the weather forecast. Data from ships, planes, radars, satellites can be collected and analyzed to build models. These models will not only predict the weather but also help in predicting the occurrence of any natural disasters. This will help you to take the right action before and save many precious lives.

data scientist

people who are experts say that data science is usually called a data scientist, whereas the definition of a data scientist is a person who manages large amounts of data, collects and analyzes large sets of structured and unstructured data.



In an organization, data scientists act as people who analyze and study patterns of data in order to obtain information, and that information will help companies make decisions.



Data scientists cannot work alone, they need the help of other personnel such as data engineers and software engineers to apply their findings to an application.