Dear Sergio Agustín Olivares,

The importance of both data science and cybersecurity will grow in the following years, as advanced technologies for information processing and data teletransmission on the Internet develop, and these issues also include the security of processing, data collection in the cloud, and data transmission on the Internet.

The importance of information technology, etc. related to the technological revolution known as Industry 4.0 is growing. This revolution is determined by the development of the following technologies of advanced information processing: Big Data database technologies, cloud computing, machine learning, Internet of Things, artificial intelligence, Business Intelligence and other advanced data mining technologies.

However, on the other hand, in recent years, the scale of cybercriminal attacks on IT systems of various institutions, including government institutions, on social media portals databases, on teleinformatic systems of banks, on electronic banking systems has been growing. Increasingly, cybercriminals are attacking mobile internet banking systems made available to Internet users, bank customers through mobile devices, mainly through smartphones.

The research shows that the scale of cybercriminal attacks on IT systems of banks, institutions etc. using social engineering connected with perfidiously created malicious software such as ransomware, ie encrypting access to data on disks or redirecting users to fake websites of banks and institutions on the Internet, is growing. the purpose of phishing of personal data, passwords of access to electronic banking accounts and, as a result, to theft of money.

The development of Business Intelligence business analytics, Blockchain technology, data analysis in Big Data database sytems, artificial intelligence to track movements and attacks by cybercriminals, prognostic analyzes etc. can be helpful in the process of improving IT risk management. Therefore, the skillful and efficient use of data science technology can be helpful in combating cybercrime, but it all depends on how these technologies will be used and who will win in the next years in this informative, information "arms race".

Best wishes

I think that it is not a zero sum game (one loses to the other)

Each will play an important role in the future. In cybersecurity we are seeing an important shift from the traditional attacks to attacks on information( which by the way is also relevant in adversarial machine learning). The interesting thing is that as attacks evolve so will the field and the skill s required to handle the emerging threats.

Data science is still in its early cycle and its development is being fueled by the hype of machine learning (ML). The evolution of data science is complex since you have to take into account its evolution from multiple perspectives such as evolving from statistics, AI, data analysis, information theory, etc.

What is in store for the next 10 years is hard to predict but in my view one has to be careful of data science more than cyber security. My assessment relies on the observation that cybersecurity has an already established number of threats that if history serves well it will not be easily solved in 10 years (we are still struggling with buffer overflows, lets not speak about disinformation propagation on social media which is more ethereal). On the other hand data science is being fueled by ML and this still needs to deliver solid results in industry to cement its worth (if not we will be going through another AI winter soon https://en.wikipedia.org/wiki/AI_winter ).

data science is emerging field and has very good scope in future, but in the while cyber security is under consider from the start of internet which will definitively grow in future hence cyber-security needs will be more and more demanding. It will left on your choice of interest then only, Personally I will go for cyber security.\

Both data science and cyber security has the future for the next 10 years.

Considering the rapid growth in value of data both fields have a bright future.

I am offering free mentorship on career paths in information security. If you would like us to schedule a call and talk about it feel free to reach out.

Combination of both is really worth. There is lot one can achieve with combining data science and cybersecurity.

Each and every organization requires this.

Please find one such application.

Preserving Electronic Health Data using Machine Learning Techniques and Cybersecurity Concerns.

Data scientists are responsible for organizing and analyzing data for a business. With companies generating more data than ever before, these professionals are in high demand ...

Those working in data science are familiar with big data analysis, machine learning, coding languages, algorithms, and problem assessment ...

"Being a successful data scientist requires a mix of technical skills, higher order thinking, and down-and-dirty problem solving," said Roger Yarbrough, principal and cofounder of marketing consulting firm Stratistry. "Given that this mix of talent isn't necessarily part of standard college curriculum, you'll find many data scientists without the necessary real world experience to fully understand the potential pitfalls you can encounter when working with data."

https://www.techrepublic.com/article/how-to-fail-as-a-data-scientist-3-common-mistakes/?ftag=TRE684d531&bhid=26515897512689358169344413145444