Even if companies have hesitated so far, they increasingly rely on a cloud-first strategy. However, hasty action can cause problems. These can be avoided with a “data first” approach. Many companies are pursuing a cloud-first strategy with their IT infrastructure. They expect more flexibility in fluctuating business trends and faster implementation of new use cases or business models. Above all, cost efficiency should not be the only priority because there is more to a comprehensive and sustainable strategy.
In addition, hopes of reducing IT costs with a cloud-first strategy are often disappointed. Sometimes the effort even increases. Because many companies fail to analyze and plan their data requirements, they later have to struggle with redundancies, loss of control and additional costs. The cause is often that many companies see the cloud as a gateway for innovation and growth. However, they have to start one step earlier. Not the cloud, but the underlying data is the key to generating sustainable added value.
Cloud-First Strategy: Data Use Without A Strategy Can Increase Risks
If companies do not recognize the need for a well-thought-out data strategy before switching to the cloud, data silos can arise. These, in turn, generate additional costs. In hybrid cloud environments, which most cloud users now use, it could look like this: In addition to workloads that remain on-premises, services from different public cloud providers are used because they usually have their specific needs, Have strengths or occasionally offer more favorable conditions.
If a provider takes over the customer’s customer’s data without a well-thought-out strategy, the effort and costs involved in ongoing operations increase in some instances. For example, data silos can arise even though the data is required for different workloads. This makes efficient use of information considerably more difficult or even impossible. Breaking up the existing silos later means a lot of extra work. In addition, if there is no data strategy – including data security and data governance – the risk for data security increases exponentially, leading to silo environments being set up without taking the defined standards into account.
If an existing customer also decides to change providers and take their data, they often only get their data back in their raw state. Because if preparatory and enrichment work for data mining has been carried out in the cloud environment, it can count as a service provided by the provider. The customer can then redeem the processed data for an additional payment at best.
The Cloud-First Strategy Must Follow Data Strategy
Data is at the heart of the digitization strategy and represents an invaluable asset for every company. This importance must, therefore, also be reflected in the infrastructure strategy. Therefore, companies should first ask themselves how to deal with their data in concrete terms. The cloud-first approach is part of the IT strategy, but it should be based on the data strategy, i.e. data first instead of cloud-first.
A good data strategy aims for an architecture in which all data can be found quickly and securely, regardless of their storage location. They should be processed across platforms and always lead to the best possible insights. Such an architecture makes it easier for the company to achieve its goals, such as increasing sales and profits and improving customer experiences. It must, therefore, not depend on a third party.
In other words, the architecture must enable end-to-end data management across all deployments – regardless of whether it is an on-premises installation, a private cloud or one of the large public cloud environments. If possible, it should also cover the entire breadth of enterprise data, from edge computing to machine learning platforms.
Cloud-First Strategy: Users Shielded From The Complexity
To set up this architecture, a hybrid data cloud is recommended. Such a data platform is designed to shield users from the complexity of data management and control and enable easy-to-use, seamless data management. In this way, companies regain sovereignty over their data. They choose the data service that suits their needs and get the most out of their data without worrying about where it is physically stored. Instead, their main task is to develop a clear vision of what their business model looks like, which use cases and processes can be digitized and what data is required for this – today and in the foreseeable future.
A data cloud can also regulate necessary functions such as data security and privacy. For example, internationally active companies must ensure that they comply with the data protection regulations of the respective markets. These often boil down to specific data not being transferred outside of a country or region. In this case, it is helpful if the data platform has a control panel that constantly monitors the data transfer and compares it with the existing rules.
Companies Can Quickly Test Use Cases
At first glance, the concept is of particular interest to larger companies because they are naturally more affected by the complexity. But on closer inspection, it’s less a question of size than one of the business models. Smaller companies often cannot afford their own IT department. For this reason, the path to the cloud seems attractive to them. Again, the underlying data strategy should determine the choice of cloud. Hybrid infrastructures, in particular, can be relevant for medium-sized companies. Initially, they will mainly use applications in the software-as-a-service model. But they also have to decide how they want to manage the constantly growing data volumes.
Finally, smaller companies are also discovering that with the help of the cloud, they can quickly test new use cases – with limited capacity and within a limited time frame, i.e. with little risk. If the project gets off the ground, requirements quickly arise that can only be met promptly within a cloud. Now, at the latest, it also makes sense to ask about data sovereignty. The sooner a company deals with the topic, the lower the risk that it will build data silos and slip into the dreaded “vendor lock-in”. Or to put it positively: A data-first strategy instead of a cloud-first approach is the silver bullet for fast and intelligent data-driven decisions – for companies of all sizes.
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