- The use of data drives the success of many of the largest technology companies such as Facebook, Google and Netflix, says Associate Professor at Noroff, Isah.
The overall amount of data is increasing. Within one year, we are now generating data that corresponds to the amount from the entire 90s.
The information comes from all sides - posts on social media, GPS, mobile phone, the Internet of Things, online sales, and more.
Finds patterns and trends
The challenge lies in how to best utilize this information.
You combine statistics, data analysis and machine learning. Mariya Chirchenkova
Big data only gets value when you analyze it using modern tools. Then companies can suddenly find patterns and trends that they did not see in their unstructured data, and leverage this to their competitive advantage.
- Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insight from structured and unstructured data. You combine statistics, data analysis and machine learning, says Mariya Chirchenkova, lecture in Applied Data Science at Noroff.
Isah A. Lawal and Mariya Chirchenkova.
Big data analysis
One of the possibilities of Big Data analysis is to get to know the customers better than they know themselves, by finding patterns and trends. Big Data, for example, can be used to find the right customers for the right goods, predict subscription cancellations or offer better customer service.
According to Mariya, a data scientist explores the data in order to find patterns and relationships that can be used.
There are so many uses of data today. Mariya Chirchenkova
- There are so many uses of data today and this list will be expanded indefinitely. For example, in Internet searches, in health care, in targeted advertising, image and speech recognition, airline planning, gaming, self-driving cars and robots.
At Noroff, a bachelors degree of applied data science is offered, either at our college in Kristiansand or via Noroff Online Studies.
The expertise and competence that an education in applied data science provides is highly sought after. There are strong indicators that data science and Big Data-related challenges will increase in many commercial sectors.
According to Isah A. Lawal, Associate Professor in data science at Noroff, data is one of the most useful resources of the 21st century.
Data for the digital economy is what oil is for the industrial economy. Isah A. Lawal
- Data for the digital economy is what oil is for the industrial economy. There is a great demand for people who can pull data from data and take their success to the next level, so the demand for data scientists will continue to grow, Isah points out.
According to Mariya, business is almost entirely dependent on data analysis for decision making and machine learning as the main components of IT strategies.
- As a result, the demand for good data scientists is growing consistently.
Requires good communication skills
- What personal qualities are required to succeed as a data scientist?
- Some of the personal qualities required to succeed as a data scientist are curiosity and creativity, because a good data scientist is a creative problem solver. Statistical thinking, because one must be able to turn data into information and thus statistical knowledge is very important in order to gain insight. Finally, good communication skills, because as a data scientist you have to be able to communicate problem and solution to a variety of target groups in the simplest way, Isah says.
You will be highly sought after in most sectors and industries that make up the job market. Isah A. Lawal
- With applied data science you will learn how to create, utilize and update relevant information from data. You will also learn how to create smart solutions for real-time data-driven problems. Thus, after graduation and with your expertise, you will be highly sought after in most sectors and industries that make up the job market, he concludes.