The “Internet of Things” (IoT) generates unlimited amounts of data. Experts assume that data from the IoT will play a relevant role in more than every second business process. Not only do private households benefit from the networking of things, but also industry. Unpredictable amounts of data make the world turn upside down. Data management helps to keep track of things.
Data lakes will continue to increase in the coming years. The data that networked devices generate has a specific value in them. 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), which illustrates the following scenario: Real-time data can, for example, positively influence the production cycles of heavy industry.
This minimizes downtime in a blast furnace, saves material costs, and reduces costs.
Because of the high value of IoT data, it is essential to access it at all times. In addition, the data must be 100 percent reliable and secure against manipulation.
Business needs are difficult to predict
The realistic forecast of business requirements is the key to corporate success and an essential prerequisite for a quick return on investment. This applies to listed, multinational corporations as well as to innovative start-ups with disruptive business models. Companies of all sizes are faced with new challenges. These include the increasing digitization of the markets, the ever-tougher competitive pressure, and a seemingly endless stream of data and new technologies.
However, these forces are not insurmountable. The technology will continue to develop consistently. Companies have to face this challenge and create new solutions that offer customers significant added value to remain competitive. 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 in the market.
The required storage capacity can hardly be planned
IoT data is primarily unstructured and can therefore be easily stored in the public cloud infrastructure. All major cloud providers provide cost-effective, scalable storage systems based on object storage solutions. With fast networks and free data access, large amounts of enterprise IoT data can be optimally stored in the public cloud.
And the public cloud has, even more, to offer: Cloud Service Providers (CSP) deliver powerful data analysis tools that absorb 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.
Correct storage of sensor data is essential
Typically, IoT devices are managed individually and remotely and act as embedded appliances such as cameras. However, this is not always the case. Many companies have distributed environments where servers in different branches monitor access to the building, control the environment or take on other company-specific tasks. The IoT network devices with which content can be created, saved and processed at many locations.
Distributed data arises outside of a company’s data center or network. The term “edge” describes computing and data management tasks carried out outside these core infrastructures. Although cloud computing has existed for many years, the technology is developing rapidly and the IoT due to the growing volume of external data. This poses significant challenges for IT departments: They have to ensure that the data is adequately backed up, assigned, and processed.
Most IT organizations know (reasonably) exactly where their data is located. However, the IoT makes it more challenging to get a firm grip on all of a company’s content. Data collected in backup sets may also contain interesting information that should be made accessible via data analysis. However, a classic backup is hardly suitable for this, as the data is not always available and access takes a relatively long time, especially for tape backups. In addition, in many cases, the value of the data may not develop optimally if all of the content is saved. For example, a camera that counts cars passing at an intersection does not store the entire video.
Instead, it is sufficient to document the number of vehicles counted in a certain period. The video data could be kept for a later date or deleted. It should also be taken into account that the data must be processed promptly. IoT devices need to decide how to use information quickly. Latency due to reading and writing of the data in a core data center cannot be tolerated. Due to these requirements, companies have to move the processing of data and applications to the edge. There they are preprocessed before they are uploaded to the core data center for long-term storage.
The “Internet of Things” leads to a multiplication of interfaces since any number of objects can be networked with one another. In addition to the primary functions of networked things, these interfaces generate large amounts of data ( big data ), which also have enormous potential. Intelligent solutions and data science are necessary to use the associated new business models.