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Working with data is developing so rapidly that we missed the moment when the «professions of the future» became our present. In this article, we discuss the predictions of what Data Science will hold in the next year.
Application of Data Science in Business
Businesses can use Data Science in a variety of ways. For example, a Durham-based real estate company analyzes more than 700 personal factors: demographics, income changes, buying behavior, and the history of each seller. These data are compared with national averages. This is how the agent knows when to contact the seller in order to have the best chance of closing the deal. Systems with similar functionality are used by American real estate companies.
Amazon has become a clear example of how useful data collection can be for the average consumer. By remembering what you purchased, how much you paid, and what you were looking for, Amazon only displays items on the home page that you might be interested in. This strategy both improves retail profitability and saves consumers money.
While machine learning models can be very useful, many business users distrust processes they don’t understand. Big data on its own is useless without analysis. Data science must find ways to make ML models more understandable for businesses.
Data Science: More and More Applications
Data Science extends far beyond retail, insurance, and fintech. We use Data Science applications every day when a social network, music streaming service or YouTube recommends content to us.
Billions of users around the world use smartphones, watches and other electronic devices, generating colossal amounts of data. Processing data from wearable trackers will allow a large number of people to develop healthy habits and prevent critical health problems. Medical data from wearable devices can help diagnose and accelerate drug development.
Farmers are using Data Science to improve the efficiency of growing and delivering vegetables, and food producers to reduce waste. Volunteer and activist organizations use Data Science to predict revenue and find ways to increase it.
Already, the number of devices connected to the Internet of Things exceeds seven billion, in seven years it is expected that their number will grow to 21.6 billion devices.
Demand for Data Science Professionals
The demand for data scientists will only grow over the next five years. For the fourth year in a row, Glassdoor has named the Data Scientist “the # 1 job in the US.” The US Bureau of Labor Statistics reports that employment in this area is expected to grow by 27.9% by 2026. According to a report from MHR Analytics, 80% of UK companies plan to hire a data scientist or seek advice on Data Science this year. However, there is not only huge demand, but also a noticeable shortage of qualified data analysts.
These are digital models of real objects. Most often they are used in industry, energy, oil production, and the automotive industry. On such models, you can make forecasts of how certain processes will take place in different conditions, test new equipment. Or conduct experiments without endangering real production.
Human body supplements
The point of such technological additions is to improve the human body and add new functions to it. For example, American companies are developing technology for chipping employees. At 32 Market, which produces vending machines for offices, employees have been implanted bioglass microchips under their skin. They replace them with a pass, credit card, and business cards. The company has now opened a separate chip development division and is working on a new device for people with dementia. The chip will help track their movements using GPS. And this is not the only example. The US Army has officially launched a chipping project for military personnel. A large microchip development company, Biohax, operates in Sweden. More than 4 thousand people have already been microchipped in the country. Chip replaces them with a metro pass and a credit card. The Swedes supply their chips to Great Britain, Germany, France, and Spain.
AI artificial intelligence in media
Artificial intelligence is also used in the media. For example, at Bloomberg, the Cyborg artificial intelligence system helps journalists in preparing articles on company reporting, the Bertie bot is working for Forbes. He helps authors with topics. Advises them on the basis of previous materials from journalists. In addition, Bertie helps with headings and matches images to texts.
And, of course, one cannot fail to mention smart machines with artificial intelligence. True, unmanned vehicles have slowed down so far. It turned out that there is still a long way to mass production, the technology is more complex than expected. But smart cars are real. For example, artificial intelligence has been embodied in additional electronics in the cabin. For example, a driver safety control system. Reduces the risk of the driver falling asleep and preventing the drunk from driving. He also informs emergency services that the driver is a danger to other road users.
AI artificial intelligence in the entertainment industry
AI platforms MuseNet and Jukedeck know how to write music. And they help composers and musicians with might and main. But artificial intelligence has proven itself especially great in creating personalized recommendations. Spotify and Netflix actively use this feature. And Amazon created the Personalize service. It helps you create referral websites and apps.
Systems that will make it possible to put routine operations on the stream and speed up development will be greatly developed. Automating tasks such as selecting and evaluating algorithms can reduce the time it takes to work with data by up to 10 times. Improving the quality of algorithms and simplifying software tools will lower the barrier to entry into the profession. These simple machine learning algorithms, decision trees, are now a breeze to deploy. And understanding frameworks like PyTorch and TensorFlow doesn’t require a PhD in mathematics at all.
In the United States, many companies use the HireVue artificial intelligence system. What can it do? To analyze the movements of applicants, manner of speech, facial expressions, posture. And also to answer questions asked by the robot. Then the system analyzes all the data and concludes whether the candidate is suitable for this position or not. According to Global Market Insights forecasts, the market for recruiting robots will grow to $ 1.3 billion by 2024. When people talk about AI artificial intelligence in HR, there are often concerns about how many millions of jobs “machines” can take. Analysts say that by 2022 it will be 75 million. This is the number of jobs that will be automated. That is, a machine or smart programs will completely replace a person. At the same time, 133 million new jobs for a person are planned to appear by 2022.
2021 brought a lot of new things to Data Science because the field of big data analytics itself is now actively developing. In 2022, Data Science will undoubtedly continue to grow and shape new trends.