Big Data

What are the main applications of Data Science?

What are the main applications of Data Science? Big Data PlatoAiStream PlatoAiStream. Data Intelligence. Vertical Search. Ai.

With 1,7 MB of data being created every second worldwide, the role of Data Scientists has become essential in almost every industry. Without the help of Data Scientists it is impossible to make sense of all this new data, analyse it and benefit from it. Let’s see in detail what a Data Scientist job entails and what impact Data Science has across industries and in our daily lives.

Today, almost all our actions online as well as in real life produce data. These very large data sets, called Big Data, are crucial information to companies of all industries. It helps them to become data driven, meaning they are able to identify new opportunities thanks to data and make decisions accordingly. To unlock the power of Big Data, however, companies need the help of a new kind of professionals: Data Scientists! Their job is to clean datasets, perform data analysis and create algorithms to deploy Machine Learning models, so machines can learn to make predictions out of new data and come up with more precise insights. Data Science and Data Scientists have proved to be useful in various industries including business, healthcare, e-commerce, internet search and social networks and new technology in general. Let’s have a look at how Data Science is helping innovation in the main industries that surround us.

Business intelligence: the most widespread application of Data Science

With Big Data, businesses are getting more and more aware that they’re sitting on a gold mine. Indeed, when processed and analysed, data collected from customers, partners, and all institutions linked with the company represents an enormous value that businesses can benefit from. As we’ve seen, Data Scientists can empower management of companies and organizations to make better decisions. Having data flowing in from every department in the company, decision makers have a precise outlook of their company’s activity and can, for instance, use that data to orientate their recruitment strategy. When data comes from outside of the company, as it is the case with Big Data, and the large amount of data coming from customers, Data Science helps organizations find when and where their products sell the best. Knowing that, they are more able to deliver the right products at the right time and meet their customers’ needs by developing new products. Data science is also a great opportunity for marketing teams to understand their audiences and drive the content they produce to offer the best customer experience possible. Finally, having a Data Scientist working out your raw data is a chance to identify data that stands out in some way, reduce fraud or create alerts when usual data is detected.

Data Science helps accelerate healthcare solutions

What are the main applications of Data Science? Big Data PlatoAiStream PlatoAiStream. Data Intelligence. Vertical Search. Ai.
What are the main applications of Data Science?

In recent years, Data Science has helped develop a variety of solutions in the healthcare industry. Data Science frameworks such as MapReduce, the programming model of the Hadoop framework, enables the analysis of huge volumes of Big Data through parallel processing. It allows artificial intelligence procedures to detect tumours, artery stenosis or organ delineation so medical teams can respond faster and put a recovery strategy into place. Data Science is also helpful in the field of genetics and genomics research. By understanding the impact of DNA, researchers are more able to find connections between genetics, diseases, and drug response. Applying Data science techniques, researchers can integrate different kinds of data with genomic data in disease research. This provides a deeper understanding of genetic issues in reactions to particular drugs and diseases and leads the way to advanced genetic risk prediction being a major step towards more individual care. Data science applications and machine learning algorithms also help simplify drug discovery processes. These processes are often highly complicated and necessitate a huge amount of time and money. Using advanced mathematical modelling, Data Science algorithms can predict how medical compounds will react in the human body without the need of lab experiments. In a nutshell, it is simplifying the prediction of future outcomes with high accuracy. Finally, Data Science helps optimize clinical processes so, in some cases, artificial intelligence can help doctors answer patients’ questions and help medical staff focus on tasks where they can’t be replaced.

Data Science applications in our everyday life

Data Science applications are not necessarily linked to a professional environment, and we’re starting to see its benefits appear in part of our everyday life. With speech recognition, Data Science allows Google Voice, Siri, and the likes to recognize your voice and make sense of what you are saying to transcribe your speech into text or into a direct computer command. If you’ve been playing Pokemon Go, you’ve been using Data Science applications as well! Indeed, augmented reality is a combination of virtual reality and Data Science. VR headset contains computing knowledge, algorithms and data to provide you with the best viewing experience. Soon, more and more aspects of our lives will be improved by Data Science. Autonomous vehicles, for instance, are using a great amount of Data Science and are in major development.

More and more companies are seeing the benefits of Data Science and using it to improve performances internally, provide customers with an optimized service or be more effective in their innovation processes. Data Scientists are therefore in high demand, and companies often struggle to find Data Science profiles to suit their needs. People looking to boost an IT career, or thinking of a career change, will be wise to discover a Data Science course.

Indeed, you don’t need to know rocket science to become a Data Scientist. Basic maths and statistical knowledge will be sufficient to join a Data Science course. Courses are often delivered in a 9 month continuous training in which you will need to dedicate 10 hours per week to the course, or a two weeks full time bootcamp training. This means you can also follow a Data Science course on the side of a professional activity. Once you are certified in Data Science, you will have the choice to work in a great variety of industries and be assured to take part in meaningful projects of great importance for our future.

Source: Plato Data Intelligence: PlatoData.io