It can be difficult to understand the abundance of information about the Data Science market. Therefore, we analyzed and collected the latest trends in the data industry.
Integration of data and artificial intelligence in all areas
Think you don’t touch the data until you work with it directly? You are wrong: today data science agency around the world is implementing AI and systems for collecting, processing and analyzing data about customers and employees. This applies to many areas:
- the automotive industry,
Today, you can predict when you will buy a car, want to change your profession, simply by collecting and analyzing data about you on the network.
In the United States in 2012, there was a public case when the parents of a sixteen-year-old girl sued a store from which they received coupons in the name of their daughter with discounts on baby products.
The complaint was that the daughter was only 16 years old, she was still a child, and the store made a mistake in target audience when setting up advertising. But it turned out that the girl is indeed pregnant, but has not yet told her parents. The store understood this with the help of artificial intelligence – the girl’s shopping preferences changed, she began to eat differently and buy pregnancy tests.
How data trends have changed business and education
The development of artificial intelligence and work with info has influenced the business processes of companies and the education market.
- There is a demand for T-shaped employees.
They not only deeply know their main specialization, but also develop in related fields. Cross-functional makes it easy for them to interact and understand the specifics of other departments.
- There is a demand for Data Scientists with little experience in this area.
According to research by HeadHunter and Yandex.Praktikum, the share of vacancies with less than a year’s work experience in Data Science is now higher than in the IT market as a whole. And over 60% of all data science jobs are for candidates with up to three years of experience. In addition, employers make a concession: if you have trained in the Data Scientist profession for a year, your training experience can be counted as a worker. You can use data analysis consultancy.
- The growth of education in the field of Data Science has increased.
It is not yet possible to obtain such a specialty in modern universities: the transformation of higher educational institutions requires much more time than the launch of a program lasting one and a half years. Therefore, the niche is actively occupied by projects of additional and online training, which try to offer relevant programs and practice-oriented knowledge.
So, over the past couple of years, Skillfactory, GeekBrains, Otus, and Yandex.Practicum have launched their Data Science programs. In Netology, the Data Science direction has existed since 2017, and now the faculty is also expanding towards cross-functionality, so it was renamed to Analytics and Data Science.
Development of generative adversarial networks
GAN – generative adversarial network – machine learning algorithms without human intervention. They are built on a combination of two neural networks: the first offers images, and the second tries to find authentic ones among them. Thus, neural networks learn by themselves.
For example, deep fake: users are prompted to distinguish images made by neural networks from real paintings. The technology also knows how to create new images by mixing the original ones. Therefore, GAN is often used in business to obtain new elements: in interior design, clothing, computer games and animation. In just four years, more than 500 such algorithms have appeared.