With unforeseen crisis piling up, the cloud remains a key investment focus for businesses. Only those who can integrate internal and external information and use it for analysis have the chance to identify risks at an early stage and take appropriate preventive measures. For a long time now, the cloud has not only been used for scalable storage of company data, but you can also rely on its advantages for creating analyses, reports, and deeper insights.
In this way, not only can normal business operations be continued – but any risks can also be identified early, and appropriate preventive measures can be initiated. In the end, precisely, this foresight represents a significant competitive advantage for companies. In practice, however, the ideas about which requirements should be the focus differ widely: while the specialist departments long for scalable and agile solutions that they can access quickly to complete their tasks more efficiently.
IT managers have concerns about what, For example, compliance with governance and compliance requirements to be able to protect databases. All of this can drastically limit access to data and reduce data quality – but this is precisely what is essential for users to be able to use modern technologies for efficient data analysis. But are these reservations valid, and how can companies overcome them to realize the full potential of the cloud?
When The Cloud’s Strengths Become Its Most Significant Weakness
Ninety-seven percent – and thus the majority of German companies – already use cloud solutions as standard or are considering doing so soon. This is the result of the current cloud monitor from Bitkom and KPMG, which shows that the cloud has become an indispensable part of the German economy. But while Gartner predicts that a proud 45 percent of investments will flow into the public cloud by 2026, private cloud solutions are still ahead in Germany – and this is precisely where the rub is regarding many existing hurdles.
A private cloud is a demand-oriented infrastructure owned by the respective company. IT professionals often gravitate towards such a solution because they strive to comply with regulatory or governance requirements. They often fail precisely because the maintenance of a private cloud turns out to be highly time-consuming. But if you stay on the ball only sometimes, in the worst case, the data quality and its security can suffer.
Regardless of the industry, every company now generates masses of data daily that must be integrated from a wide variety of sources. New information is generated through websites and apps that prospects interact with during the buying process, as well as through IoT devices and sensors that can track manufacturing and supply chain processes, as well as escalator maintenance – and more sources are constantly being added.
With cloud solutions, handling this vast amount of data is possible. However, suppose these are hoarded in silos without formulating a precise goal. In that case, the most significant advantage of the cloud, which is the cheap storage of large amounts of data, can develop into a severe problem. All of this impedes the flow of data and slows the effects of the real-time, data-driven decision-making required for long-term organizational profitability.
There Is Still A Wide Gap Between Desire And Reality
Companies in Germany often see the cloud as a kind of filing cabinet that makes it possible to collect large amounts of data more conveniently than was previously the case with on-premises solutions. However, if they want to stay caught up in international comparison, it is high time to change this attitude. The number of new and potentially unexpected disruptions, which has increased sharply in the past two years, makes it all the more necessary to find new approaches to increase the agility and resilience of companies.
However, many managing directors are still treading water. Suppose the past two years have shown anything. In that case, access to historical trend data is crucial to analyze and model what might happen in the future, identify likely risks and prescribe possible opportunities and actions to improve future agility.
This is proven, among other things, by an IDC study commissioned by Alteryx: It turned out that 62 percent of professionals are already expected to be able to make agile and scalable decisions based on data – in the medium to high range positions; this requirement is even placed on 75 percent of employees. Unfortunately, many still need more tools and expertise to make this requirement a reality.
At the same time, there is increasing pressure on experts who already have sufficient data expertise. They are expected to carry out precise analyzes in a short time that generates real added value for the company – they are often more concerned with mastering large amounts of data. For companies to realize the full potential of the cloud, this gap must be closed as quickly as possible because the most significant opportunity for the cloud lies in combining two things.
Cloud-based analytical modernization initiatives to give more employees more accessible and faster access to more reliable data, on the one hand. And they are delivering accessible analytics through easy-to-use, no-code/low-code technologies to enable the flexible discovery of insights necessary for success. Only by taking full advantage of the storage and massive computing power available in the cloud will more employees have access to deeper insights.
Cloud-Based Data Analysis As A Collaborative Process
It is no coincidence that Gartner predicts a real triumph for the public cloud internationally. Since external providers are responsible for maintaining the infrastructure here, the workload for companies is reduced, with it, the risk of overlooking potential security risks. In addition, a public cloud is easier to scale than a private cloud and can therefore be flexibly adapted to a company’s changing needs. In today’s business world, this flexibility is essential. Companies must expect new disruptions to occur at any time.
This makes it all the more critical for them to be able to access trustworthy information and derive quick insights from it. To ensure this, it is essential that everyone – from IT to the specialists in the individual departments to the data scientists – pulls together. With people able to extract new insights from raw data, companies can be transformed to meet today’s challenges or anticipate tomorrow’s.
If data is the oil needed to generate business-relevant insights, then data-savvy employees are the engine that powers this process. Insights and innovations that were previously unimaginable become tangible. Ultimately, data and their analysis are becoming more accessible through cloud-based solutions. With faster execution and ease of use of browser-based self-service tools, everyone can put data analytics at the heart of their decision-making.
For this to succeed, however, companies must ensure that the data used is always up-to-date, high-quality, and comes from a wide variety of sources. This requires a collaborative approach where everyone speaks a common language of data. Only in this way can subject matter experts work effectively with the IT department and the small number of data scientists available to train algorithms and models to ensure that data analysis can take place at every level. Ultimately, it is all of these steps that lead to a more robust data infrastructure.
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