Data science is a large amount of diverse structured and unstructured information that moves at incredible speed and is difficult to analyze using traditional methods and technologies.
This is especially true of the corporate world and all companies regardless of their industries and the countries with which they work. In the digital environment, companies are gaining incredible amounts of information about their users and customers. For example, data about user behavior, their social and cultural background, various preferences in food, clothing, entertainment, political views, as well as purchase history and other personal information.
This is especially true of the corporate world and all companies regardless of their industries and the countries with which they work. Despite the vast amount of diverse data, companies still do not know how to use it to satisfy the interests of both users and themselves.
In such cases, scientists and science come to the rescue.
What is data science and what scientists do
It is an interdisciplinary science that exclusively uses scientific methods, processes, algorithms, statistics, modern technologies and complex systems to deeply understand data and information.
It is called interdisciplinary science because it is based on theories, methods, and practices from different fields of knowledge – mathematics, computer science, computer science and many others. It also uses machine learning, data analysis, data science services consulting, statistics to get reliable results from different information.
Therefore, it is not hard to guess that scientists are specialists who are well versed in data analysis, and have the appropriate technical knowledge and education, as well as the necessary skills to solve complex problems.
Why data science is needed
However, “getting or extracting information from data” can be a rather vague explanation for the importance. Data science can answer many priority and important questions, such as:
- Who should companies sell their products and service to?
- Why is this particular product selling poorly?
- How many new users will there be in the next month, year, etc.?
- What features will make the company’s website more user-friendly?
It can provide comprehensive and accurate answers to these and other questions that ultimately lead a company to success. Since the correct answers to the questions will ensure competitiveness and significantly improve the quality of customer service and increase the level of satisfaction of their users.
Data Science Use Cases
It has many good examples. For example, almost everyone loves to watch TV shows and movies, especially on Netflix. Netflix is currently the largest company in the entertainment industry. It has more than 147 million users in 190 countries around the world, and the company’s revenue exceeded $ 15 billion in 2018.
So what is behind the company’s success? The answer is pretty simple – data science. Netflix uses an effective recommendation system. For example, if you are watching Stranger Things, the system will most likely tell you to watch a similar show, such as Altered Carbon. Netflix knows what you like. After analyzing your preferences and interests, the recommendation system will suggest exactly those films and series that you most likely will like.
Facebook is another company that actively uses it their business. The company uses it to help other companies target their customers correctly. By analyzing information about users, such as demographic data, geolocation, and user behavior, Facebook can serve relevant ads to specific users.