Recommended response
Posted: Wed Feb 12, 2025 7:12 am
Recommended response: It is recommended to create sufficient internal IoT automation solutions to close the gaps that exist with vendors.
The IT requirements of IoT devices are very comprehensive and cross-vendor. To date, there is no sufficient automation from vendors for network and security controls required for large IoT projects.
Anyone who wants to ensure the security of IoT networks on a large scale should therefore commission their own technical management to develop the necessary automation solutions. This will not work without internal managers: External providers cannot develop solutions quickly enough to handle all the unplanned security tasks that become necessary due to the Internet of Things.
Companies have a wide range of possible uses for the Internet of Things: In retail, for example, IoT technology can be used to improve warehouse logistics and supply chain . In stores, temperature sensors can ensure that vegetables stay fresh, or RFID chips can make it possible to automatically register the contents of a shopping cart. According to Forbes, 70% of retailers plan to invest in the Internet of Things.
To enable such connectivity, each retailer must build a system of computers, networks and devices that communicate and share data in real time. Cross-platform IoT solutions do not yet exist.
Security risks often arise within the company, and security solutions are best developed internally. Technical leadership can use microsegmentation to create secure areas in data centers and networks and isolate and protect individual workloads within the IoT ecosystem. It should be clearly defined what IoT security requirements exist and how they will be implemented using these and other measures.
The availability of data scientists
The challenge: In the field of data science, demand far exceeds supply.
Data specialists are in high demand: they are currently one of the most sought-after professional groups worldwide and in Germany there are a total of 95,000 unfilled positions. The number of job advertisements for data scientists in the USA increased by a full 650% between 2012 and 2017 .
The sheer volume of data generated every day alone highlights the importance of good data experts: 90% of all data available worldwide is less than two years old , and this is largely due to the increase in IoT devices and the data sets they generate. Data scientists who can analyze and interpret complex digital data are essential for the successful use of IoT applications.
In the USA, well-trained data scientists can earn up to $170,000 a year , and even though the average salary in Germany is significantly lower, it is still over €50,000. The career path of data scientists is therefore extremely promising, but it may be difficult for companies to find suitable talent on the job market for a few years to come.
In addition to a person for technical management, a data scientist is also indis oman telegram data pensable for IoT management. The shortage of skilled workers, misconceptions about the job profile and tight budgets for wages often put additional obstacles in the way of companies.
The process of IoT implementation, just like hiring a data scientist, should be gradual and deliberate .
Go
Run
(over) flying
Before you hire a data scientist (either full-time or as a contractor), you should be clear about the important role he or she will play on your IoT team. If you're not sure about this, you should first figure out how exactly your team will use data science.
The most important aspects of the data science roadmap for your IoT project are not related to mathematics or technical considerations, but to business strategy. The roadmap should be designed by someone who has a strategic vision for the impact of the Internet of Things on the business.
The IT requirements of IoT devices are very comprehensive and cross-vendor. To date, there is no sufficient automation from vendors for network and security controls required for large IoT projects.
Anyone who wants to ensure the security of IoT networks on a large scale should therefore commission their own technical management to develop the necessary automation solutions. This will not work without internal managers: External providers cannot develop solutions quickly enough to handle all the unplanned security tasks that become necessary due to the Internet of Things.
Companies have a wide range of possible uses for the Internet of Things: In retail, for example, IoT technology can be used to improve warehouse logistics and supply chain . In stores, temperature sensors can ensure that vegetables stay fresh, or RFID chips can make it possible to automatically register the contents of a shopping cart. According to Forbes, 70% of retailers plan to invest in the Internet of Things.
To enable such connectivity, each retailer must build a system of computers, networks and devices that communicate and share data in real time. Cross-platform IoT solutions do not yet exist.
Security risks often arise within the company, and security solutions are best developed internally. Technical leadership can use microsegmentation to create secure areas in data centers and networks and isolate and protect individual workloads within the IoT ecosystem. It should be clearly defined what IoT security requirements exist and how they will be implemented using these and other measures.
The availability of data scientists
The challenge: In the field of data science, demand far exceeds supply.
Data specialists are in high demand: they are currently one of the most sought-after professional groups worldwide and in Germany there are a total of 95,000 unfilled positions. The number of job advertisements for data scientists in the USA increased by a full 650% between 2012 and 2017 .
The sheer volume of data generated every day alone highlights the importance of good data experts: 90% of all data available worldwide is less than two years old , and this is largely due to the increase in IoT devices and the data sets they generate. Data scientists who can analyze and interpret complex digital data are essential for the successful use of IoT applications.
In the USA, well-trained data scientists can earn up to $170,000 a year , and even though the average salary in Germany is significantly lower, it is still over €50,000. The career path of data scientists is therefore extremely promising, but it may be difficult for companies to find suitable talent on the job market for a few years to come.
In addition to a person for technical management, a data scientist is also indis oman telegram data pensable for IoT management. The shortage of skilled workers, misconceptions about the job profile and tight budgets for wages often put additional obstacles in the way of companies.
The process of IoT implementation, just like hiring a data scientist, should be gradual and deliberate .
Go
Run
(over) flying
Before you hire a data scientist (either full-time or as a contractor), you should be clear about the important role he or she will play on your IoT team. If you're not sure about this, you should first figure out how exactly your team will use data science.
The most important aspects of the data science roadmap for your IoT project are not related to mathematics or technical considerations, but to business strategy. The roadmap should be designed by someone who has a strategic vision for the impact of the Internet of Things on the business.