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Data Science: How Data Is Transforming Key Industries
05 de July de 2022
Fifteen years ago, on June 17, 2007, Steve Jobs presented the first iPhone. Smartphones have changed everything since then and, from 2010 until now, the digital transformation process and datification have been gaining ground exponentially. Currently, we all continually produce data through the devices we own that are connected to the Internet, which has laid the ground and will continue to lay ground for a revolution and a change in paradigm that affects a great number of sectors.
The amount of data being created, captured, copied and consumed is expected to double in the next three years, reaching 180 zettabytes by 2025. This is expected to have a great impact, bringing disruption to key industries. And data will be at the centre of it all. That’s why, Data Science has become so relevant when it comes to understanding, anticipating and getting on board the transformations that are already taking place in this process that’s already being called the 4th Industrial Revolution.
What’s Data Science?
Data science brings together the techniques we use to turn data into information and into knowledge in order to create models, predictions or applications that add value. For years, a great amount of data was left unused because no one knew what to do with it. As time went by, it became crucial to know how to read them and use them in different businesses.
Marketing and commerce, for example, were the first areas to understand that knowing how to play around with the huge amount of data that surrounds us, thanks to the population’s constant connection to the internet, has become the best asset. Big data, analytics and digital transformation have harmonised the complexity of the data collecting process in an environment in which codification and programming will become less and less necessary.
From Home to the Stores: Some Implementations
The areas in which data science is already being implemented or will be implemented to boost the development of new technologies and businesses are countless; among them, home automation. These are some of the most relevant ones:
-Finance: Models for investment, credit risk and insurance are already based on data science. In the coming years, it will also gain prominence in the fight against fraud in blockchain environments.
-Retail: Commerce is one of the areas where there’s more room for disruptiveness, whether around marketing, operations, supply chain or sales. Manufacturing will also see an increase in efficiency and quality control.
-Infrastructure: Self-management and the maintenance of great infrastructures are some of the challenges that data science has to face. The same happens with everything related to the development of smart cities and home automation.
Big Challenges for Data Science
The great amount of data that we have —which won’t stop increasing in the coming years— requires specialised algorithms and software. This process is becoming increasingly heterogeneous and complex. Getting data to interact with other data makes it possible to automate decision making.
Another challenge, for companies, is the fragmentation of data sources. Managing to add data from different areas into one omnichannel strategy, cross-matching and standardising them will increase efficiency and the ability to predict models. 5G is also crucial for guaranteeing the collection of data in real time and with no latency, which will help us process information faster in order to get quick answers.
Some Skills that a Good Data Scientist Must Have
Data scientists are currently being compared to computer scientists of the end of the 20st century. Of course, there are no questions about their importance for their coming years, in which they will become one of the most highly demanded profiles. These are some of the skills that a good data scientist must have:
-Knowledge and passion for maths and statistics.
-Excellent programming skills to filter and clean up data.
-Predictive thinking.
-Communication skills to inform results to non-technical staff.
-Understanding your own company’s business model.
Data science is experiencing a great boom in face of the exponential growth of data and the population’s constant connection to the internet, which in turn result in big transformations in strategic industries.
Article written in collaboration with Marc Sansó, Tech-Management Consultant, CEO at Elsebits and a professor at EAE.