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 different cloud services

Cloud services make it possible to establish the connection between a wide variety of content and the user. But how do the cloud technologies differ and what is important when integrating such a solution in daily operations?

Saas

In the Service as a Software approach, software applications are provided by a service provider via the Internet. Here, users can practically subscribe and access the stored data via the web.

PaaS

The platform-based approach PaaS enables cloud use for the development and provision of applications. At this point, the provider makes the necessary infrastructure available to carry out the developments.

IaaS

For the Infrastructure as a Service approach, the customer has access to storage, servers, individual network components and many other IT resources. These are made available via the cloud and can be billed based on actual use.

Types of cloud services

Cloud technologies are creating many new practical possibilities for everyday storage. However, there are concrete differences here that become noticeable depending on the type of data. The following differences should therefore be noted around the cloud approach.

Public Cloud

A public cloud is an open and unlimitedly available solution. This includes, for example, the providers Dropbox, GMX mail or Google Docs, as many customers share a common infrastructure. This makes data protection much more local and transparent to oversee without developing new challenges.

Private Cloud

A private cloud is only accessible to the internal company. This creates a secure environment, especially for important and specific content, with which important details are not at risk. Scalability also plays a decisive role in the private cloud, which means that growth can be adapted exactly to the wishes of the users.

Hybrid Cloud

Hybrid clouds combine public and private access. In this way, simple and non-critical applications can be stored via the public cloud, while important and specific data about the company can be stored in the private environment. This gives each user the necessary flexibility to decide which form of storage is suitable.

Community Cloud

A community cloud is an interesting and helpful tool for collaborative projects. In this case, the users are able to let a firmly defined group of users access the contents of the cloud. Thanks to the simple and flexible setting, this group of people can be redesigned for each project in order to rely on customised solutions.

Virtual Private Cloud

A virtual private cloud is a technology in which a private cloud is located in a public cloud. This allows the many benefits of a virtualised network to be accessed while ensuring data security. The virtual private cloud can therefore provide more practical convenience.

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.

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.