Industry 4.0 generates immense amounts of data. In order for companies to make their production even more efficient, they need to mine and use these data treasures. However, there is still a great deal of fear when it comes to handling data from the Internet of Things (IoT), which poses enormous challenges for IT managers.

Store and manage sensor data correctly

More and more devices have access to the internet and produce huge amounts of sensor data. Typically, IoT devices are managed individually and remotely, acting as embedded appliances such as cameras. However, this is not always the case: many companies have distributed environments in which servers in different branches monitor access to the building, control the environment or perform other company-specific tasks. The IoT networks devices that can be used to create, store and process content at many locations.

Distributed data often originates outside a company's data center or network. The term "edge" describes computing and data management tasks that are performed outside these core infrastructures. Although cloud computing has been around for many years, the technology is evolving rapidly along with the IoT due to the growing volume of external data.

These new developments present IT departments with major challenges: They need to ensure that data is appropriately secured, mapped and processed. While most IT organizations know (reasonably) exactly where their data is located, the IoT makes it more difficult to get a secure grip on all of a company's content. This also has an impact on data protection and compliance with regulations such as the European General Data Protection Regulation (GDPR).

As so much information is generated at the edge of the infrastructures, it is difficult to move the data to a data center for processing. Due to the large number of devices used, this can only be achieved with high investments in external networks.

Furthermore, in many cases, the value of the data may not be maximized if the entire content is stored. For example, a camera that counts cars passing at a road junction does not need to store the entire video. Instead, it is sufficient to document the number of vehicles counted in a certain period of time. The video data could still be stored for a later date or simply deleted.

It must also be taken into account that the data must be processed promptly. IoT devices must decide quickly how to process information. Latency caused by reading and writing data to a core data center cannot be tolerated. Due to these requirements, companies must move the processing of data and applications to the edge. They are pre-processed there before being uploaded to the core data center for long-term storage.

IoT data is usually unstructured and can be easily stored in the public cloud infrastructure. All major cloud providers offer cost-effective, scalable storage systems based on object storage solutions. With fast networks and free data access, large volumes of enterprise IoT data can be stored optimally in the public cloud.

Using data correctly and deriving value from it

And the public cloud has even more to offer: Cloud Service Providers (CSP) deliver powerful data analytics tools that ingest and process large amounts of unstructured content. This enables companies to develop highly scalable ML/AI applications to process data more efficiently than in a private data center.

The data that networked devices generate has a certain value. The data streams in the IoT should therefore be available in real time. This is the only way for companies to benefit from the latest information at all times. This also applies to the Industrial Internet of Things (IIoT). Real-time data can have a positive impact on production cycles in heavy industry, for example. This can minimize downtimes in a blast furnace or save material costs.

Due to the high value of IoT data, it is extremely important to be able to access it at any time. In addition, the data must be 100% reliable and securely protected against unwanted manipulation.

Olaf Dünnweller is Area Vice President Territory Sales EMEA and Managing Director Germany at Commvault. © Commvault

Realistic forecasting of business requirements is the key to corporate success and an important prerequisite for a rapid return on investment. This applies to listed multinational corporations as well as innovative start-ups with disruptive business models. Companies of all sizes are confronted with new challenges. These include the increasing digitalization of markets, ever tougher competitive pressure and a seemingly endless stream of data and new technologies.

However, these forces are not insurmountable. Technology will continue to evolve. To remain competitive, companies must rise to this challenge and develop new solutions that offer customers decisive added value.

Many IT providers now have strong partners at their side to help companies integrate the right solution, including system integrator and digitalization expert Kramer & Crew. The close collaboration opens up new possibilities and the latest technologies for end users.

Manage data securely

Data lakes scare many companies - but the Internet of Things also offers enormous opportunities and competitive advantages. The IoT is forcing companies to rethink their IT and business processes. Those companies that successfully master the management and security of their data and generate sustainable value for their business will prevail on the market. To do this, however, the resulting data must be managed correctly: The best way to do this is through edge computing and back-up in the cloud and with the right partners.

Olaf Dünnweller, Area Vice President Territory Sales EMEA and Managing Director Germany at Commvault / ag