The cloud, a decentralised data storage facility, can be found almost everywhere today. Every smartphone can use cloud storage to store and manage photos there, for example. The cloud also plays a central role in many data science projects. Because once a promising use case has been found, the existing IT infrastructure often proves to be a bottleneck. Is the existing computing and storage capacity sufficient? Is it worth the sometimes considerable investment to be able to store and process large amounts of data? What if an innovative approach cannot be permanently integrated into the company? What happens to the technology that is no longer used?

Sometimes fail Data Science Projects in such considerations. But there is a simple solution: the cloud. This plays a particularly important role in the context of Industry 4.0 and mobile use cases.

Reason 1: Scalability on demand

Anyone who operates their own server or IT infrastructure must ensure that sufficient computing power and memory is available for all kinds of enquiries and tasks - not only currently, but also in the long term. So far, however, too few companies have Data Engineerswho take care of this task.

A critical The challenge is scalabilityWhen it comes to growth or unanticipated demand, thee goes. If, for example, a new service is introduced that is to be usable by all customers from one day to the next, the complete IT infrastructure must first be be adapted for this purpose. This is because data traffic can increase considerably when new and, above all, networked products or services are introduced.

The situation is different when companies thereby rely on Cloud services set. If the demand grows - even unexpectedly or abruptly - more storage space or computing power is simply added. The cloud offers ideal conditions for scaling business models or individual use cases. Even on demand, if need be.

Reason 2: Outsourcing of IT and security tasks

The second important advantage, which is more or less automatic, comes when companies rely on the cloud: They not only outsource the IT infrastructure, but also time-consuming and labour-intensive tasks. Independent of the respective provider, the cloud service providers take on three important tasks that companies would otherwise have to take on themselves at great expense:

• the continuous backup of the data
• the updating of the hardware
• and Cyber Security

The latter is an often underestimated and sensitive aspect of data projects. The basic principle is that all Datathat are outsourced to the cloud should be encrypted in order to protect them from Protect against unauthorised access. But the cloud provider itself will also do its best to protect its customers' data from attacks, as its business model depends on it. Against the background of the European Data Protection Regulation (DSGOV), which came into force on 25 May 2018, the cloud is also an interesting option.

Among other things, it is mandatory for companies to protect data from damage and loss as of this date. Those who store their data securely in the cloud have an additional guarantee that the data will not be lost. As a rule, professional providers create one or more backup copies of all data.

Reason 3: More agility

The IT infrastructure plays a central role in the topic of agility. But the size of the company is also an important factor - the larger a company is, the more rigid structures become and the agility as well as the Innovative capacity decreases as a result. Smaller teams and start-ups have a strategic advantage here. However, the cloud represents an interesting solution approach for larger companies in this respect.

Independent of existing structures, the cloud offers a basis to, for example develop new products and test them on the market. With increasing success, the projects can simply be scaled up and the capacities adapted from the cloud. Strongly expanding companies such as Zalando, which want to grow quickly on the one hand and still remain innovative, used this strategy.

Reason 4: Quick access to data

In the context of industrial production, toog it can be worthwhile to rely on the cloud. Speed advantages are derived from the networking structure alone. Instead of having to integrate the individual components of a Smart Factory on-site with each other, all machines can be networked via the cloud. This reduces the complexity of the network structure and the Access speed is increased.

But the cloud brings many more advantages. Not only the processing speed, but also the degree of networking within a company increases. This also makes it easier to network several locations with each other. Finally, the clarity of data stocks also increases when data is not stored in different places in the company but is bundled together in one place. The risk of Silo formation thus decreases drastically.

The advantages and disadvantages of cloud technologies

Those who opt for cloud technologies benefit from maximum scalability. This means that the new systems and solutions can be customised down to the last detail, making the storage and retrieval of information much more flexible. As a result, the IT administration effort can be significantly reduced, making storage more practical. The new approach means that only those services are used that are really necessary.

One of the disadvantages of cloud computing is the regular commitment to fixed conditions. As soon as monthly payments are no longer made, the stored content is no longer available. In addition, retrievability is linked to the available internet. Unfortunately, there are still gaps in the supply that make data retrieval difficult.

For a comprehensive look at the use and integration of cloud computing, read our blog post:

Cloud computing: explained compactly

Conclusion:

The cloud thus presents itself as a Ideal solution for data science projects The result. Without having to make high investments before the proof-of-concept, capacities can be increased if the test is successful and demand increases. Scalability makes costing easier and thus brings the possibility of promoting agility and innovation even in large companies.

The important topics of maintenance and performance are outsourced and are the responsibility of the cloud provider. And also with the topic of Data security companies benefit from additional protective measures that providers take. Through the cloud, this total package enables a lean team to act in an agile manner. This makes data science projects a realistic and highly interesting option for companies of all sizes.