Can data scientists tackle the IoT demand?

Current and future data scientists should consider the impact IoT will have in the field, especially because companies investing in IoT will need data experts

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The world of IoT (internet of things) is growing fast. “Smart” devices are popping up all over the place, from tiny chips to large manufacturing machines; almost every industry is touched by the revolution of IoT. Technology company Ericsson predicts that by 2018, there will be more IoT gadgets than mobile phones. Intel forecasts there will be 200 billion connected devices by 2020. It’s clear that the IoT world is growing at an unprecedented pace, changing the way many industries work.

Accenture estimates the IoT industry could add $14.2 trillion to the global economy by 2030. IoT’s reach will spread across various fields:

  • Smart cities will have an annual growth rate of 54 percent over a six-year period.
  • 60 percent of global manufacturers will analyze processes and identify optimization possibilities using analytics produced from connected devices.
  • 75 percent of new cars will come with built-in IoT connectivity by 2020.
  • The connected health market will reach $36 billion by 2024.

With all this potential, it’s no wonder companies are investing big in IoT. The problem currently is that businesses are struggling to find employees who can handle the world of IoT.

The IoT skills gap

According to a Teksystems survey, 45 percent of IoT companies struggle to find security professionals and 30 percent report having difficulty finding digital marketers. Furthermore, although most organizations expect IoT initiatives to have a high level of impact on their business over the next five years, only one in five organizations have moved to implement IoT projects.

The burgeoning problem is that companies cannot find qualified talent to work on IoT, which means their progress in IoT is becoming stalled. Inmarsat interviewed 500 senior IT decision makers from major organizations, of whom 46 percent identified a deficit of staff with experience in analytics and data science.

Data scientists helping to fill IoT positions

While other expertise, such as cybersecurity, is needed to fill IoT staff positions, data scientists can pick up a lot of the slack concerning the IoT skills gap. According to CIO, the top 10 most in-demand skills for IoT are machine learning, AutoCAD, Node.js, security infrastructure, security engineering, big data, GPS development, electrical engineering, circuit design, and microcontroller programming. Data scientists encompass many of these skills—especially the first, machine learning.

What’s more, IoT will produce massive amounts of data. For example, annual global IP traffic passed the zettabyte (1000 exabytes) threshold in 2016. An agile infrastructure will be necessary to manage the vast amount of data, and who better to manage it than data scientists?

Finding qualified candidates who can read and analyze the data across different devices and machines will be difficult as well. Data scientists, however, will be able to fit into these roles with their background in managing big data and experience managing large sets of data.

As new, enormous sets of data emerge with IoT, employees will be needed to explain the data to make strong business decisions, as well as sound technical decisions. IoT-sourced data will most likely merge with traditionally sourced data, creating the need for a unified data management strategy across the company.

Another data problem that could emerge with the surge of IoT is data ownership. Of the data collected, who owns it—the company or the consumer? Data scientists who currently work in security and ownership areas can help solve these problems, making it clear who owns and has access to what data.

The future data scientist: IoT expert?

Businesses that plan to invest in IoT should consider the impact on data and who can address this impact internally. Companies will have to go through immense internal changes to handle the amount of data coming in from IoT sources, which means someone will need to manage this shift. Data scientists working with IoT will need to know how to analyze massive data sets, what to look for in the data, and how to make productive business decisions based on findings.

Current and future data scientists should consider the impact IoT will have in the field, especially since companies investing in IoT will need data experts. Although the job of data scientist is highly in-demand, soon we may see an even greater need for data scientists to work on IoT teams.

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