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The Role of Data Science in 5G

With each day technology has been advancing. The things that were a dream of yesterday have become the reality of today. And with the thought of making our lives smart not only by making us smart but also our environment too, 5G was introduced in late 2017. 

Well before moving ahead with 5G and its impact when mixed with data science, let’s first understand what 5G is.


5G is nothing but a new global wireless standard network. It was rolled out after the introduction of 1G, 2G, 3G, and 4G, where G here stands for “generation”. It was introduced with the sole purpose of connecting everyone and everything virtually including machines, objects, and devices. With features such as higher speeds, little-to-no latency, and superior reliability, 5G will be impacting almost every industry from transportation to healthcare to agriculture to logistics and many more.


Let’s move forward to the part of data science and its role in 5G.

Data Science and 5G

Our lives, our lifestyles, and the way we live are gonna get changed drastically with the involvement of data science and 5G, facilitating connected devices as well as automation systems with real-time data exchange. The dreams of having smart cities, self-driving cars, AR/VR, smart healthcare, massive IoT, and smarter AI will be a reality now. 

With such a high speed of data transmission combined with the power of low latency and mobile edge computing (MEC), which means downloading and uploading data faster than ever before has laid out the foundation for technological developments called Industry 4.0 benefitting analysts to collect, clean and analyse large data volumes in a shorter period of time. For example, a movie of size 4GB which took 27 minutes to download over 4G will take about a few seconds to download with 5G.

With the roll-out of 5G and the involvement of data science, it has even let us make our networks intelligent. Network analytics will let us build a flexible 5G network by providing a simplified operational complexity. The analysis of the utilisation of the network and the patterns in real-time traffic data will be based on machine learning algorithms and will be decided by Network Planning and Organisation (NPO) on where to scale network functions and application services which would have been an afterthought until today.

Some of the key features of Data Science in 5G for business drivers include:

  • Mobile Edge Computing (MEC): The connectivity of different devices such as sensors or gateways or controllers backed with distributed systems allows the real-time insights with actionable intelligence. The most important aspect is dynamic network slicing, thus, providing slicing-based traffic prioritisation. 
  • Data Monetisation: Well, the full economic effect of 5G will be realised by the world by 2035 but the impact of it can be seen today as well. For example, the concept of self-driving cars was not even a reality before 5G was in the picture. With the expected potential growth of about $13.1 trillion support as goods and services and 22.8 million jobs alone, only time can tell the actual effect of 5G on the economy.
  • Predictive Maintenance: As one of the important and leading use-cases of Industry 4.0, the prediction of failures before they could occur by leveraging AI would help in predictive maintenance. For example, in July 2021, Pentagon stated that they have equipped their prediction systems such that they could predict disasters happening beforehand, thus, buying the time for help in that region.
But with great responsibilities comes great challenges. So, some of the key challenges that will be encountered while laying the path for combining data science and 5G would be:
  • Data and High Speed for Data-in-Motion: The data pumped by the smart healthcare or cities, self-driving cars, and large-scale industrial IoT will be in petabytes in just a few minutes, so super fast lightning support will be needed to read/write data. Also, the type of data (labelled or unlabelled) will be crucial to decide which type of learning needs to be done.
  • Security: The alarms that Big Data raises on end-to-end security are important to safeguard enterprise data or user privacy with no compromise. Thus, building a robust 5G secure infrastructure is crucial.
  • Real-Time Insights: Even having negligible latency by providing lightning-fast data transmission and multi-edge analysis, being one of the critical requirements of 5G, the real-time actionable insights is still a big concern in mission-critical applications such as security surveillance, public safety, and emergency care.

Well, it is still a far-eye vision to encounter the full functionalities of 5G and its impact when combined with Data Science as some areas of the network are still yet to be experimented. But despite that, the mixing of analysis and 5G is indeed going to disrupt the way of living by facilitating Industry 4.0 technology. The combination of sophisticated technologies, such as IoT and ML with 5G network services provides tonnes of data allowing more than just real-time data analysis and insights. Thus, we can conclude by saying that these technologies clubbed with 5G will play a key role in enabling AI everywhere.

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