Tackling Multi-Cloud Data Challenges: Strategies for UK and Ireland Enterprises

In today’s digital age, businesses are generating vast amounts of data, and storing and analyzing this data has become crucial for businesses to operate effectively. To manage this data, many organizations are turning to cloud infrastructure, specifically multicloud systems. Multicloud, which is the use of multiple cloud services from different providers, promises more flexibility, scalability, and resilience. However, like anything else, there are challenges involved in multicloud deployment.

Report on Multicloud Challenges

According to a report sponsored by SAS and titled “A Silver Lining from Every Cloud,” decision-makers in most enterprises in the United Kingdom and Ireland face significant challenges in handling data across multiple clouds. The report emphasizes that adopting multicloud has not made things better for organizations, but has instead introduced a multitude of challenges that can affect the efficiency and effectiveness of business operations.

Common complaints are poor accuracy, high costs, and slow speeds

The report highlights several common complaints faced by enterprises using multicloud solutions. These complaints include poor accuracy, high costs, and slow speeds. Poor accuracy means that enterprise executives often encounter multiple answers to the same question, depending on where the cloud data resides. High costs are also a concern as multicloud solutions are not always as cost-effective as expected. Finally, slow speeds mean that time-sensitive analytics cannot be generated quickly enough from cloud data.

There are problems associated with multicloud

Organizations are committing to multicloud options to manage data, yet the report shows that it is not making things better. When enterprises use different clouds to manage various kinds of data, it can develop a multi-layered structure where data is scattered and silos are created. This data then becomes inaccessible and difficult to manage. This situation results in an organization having multiple answers to the same question, and there can be a delay in generating analytics because of the need to search for data residing in different cloud deployments.

Integration of data platforms

The result of a complex cloud deployment is a set of data platforms that require better integration. Enterprises need to take a proactive approach to data integration. However, the lack of planning and internal cooperation often leads to fragmented data management and siloed systems.

Solution to Multicloud Problems

The solution starts with building a data strategy from the ground up and being intentional about where and how to store, secure, access, manage, and use all business data, regardless of where it resides. Furthermore, decision-makers need to focus on implementing data management policies and procedures that allow for easy access without compromising data security, governance, or compliance. The lack of an actual plan stating where and how the business stores, manages, and uses data is the problem. However, the absence of a plan doesn’t mean that implementing a complex cloud deployment is wrong. It merely means that planning is critical.

The future of multicloud

Enhancements in cloud storage and computing technologies mean that businesses will face a significant number of opportunities and challenges when managing data in the cloud. It is likely that organizations will continue to struggle with complex and inefficient data usage, including security, governance, and compliance, unless more proactive measures are adopted. We need to be much more proactive about technology planning, starting now. The report shows that there are significant benefits to using multicloud, but only when combined with a comprehensive data strategy, policies, and procedures. When done correctly, a multicloud deployment can provide the flexibility, scalability, and resilience that businesses need to thrive in today’s global market.

As organizations increasingly look to the cloud to store and analyze their data, it is clear that multicloud has become a vital option. However, with the flexibility and agility come problems in deploying and handling data across multiple clouds. By putting data management at the center of the cloud strategy with the help of a comprehensive data strategy, policies, and procedures, businesses can maximize the power of multicloud while avoiding the inherent risks that come with it. In the end, meticulous planning and proactive measures are necessary to ensure cloud deployments continue to be beneficial to organizations.

Explore more

Modernizing Storage for Real-Time Analytics and AI

The exponential growth of data-intensive workloads has fundamentally transformed the storage layer from a static back-end utility into a high-velocity engine that dictates the success of modern artificial intelligence and real-time decision-making systems. In the current landscape of 2026, the efficiency of an algorithm is no longer the sole determinant of analytical success; rather, the underlying infrastructure must now support

Using Premortems to Avoid Data Modernization Pitfalls

The moment a billion-dollar data architecture project receives final approval is usually the same moment that the hidden seeds of its eventual collapse begin to sprout beneath the surface of organizational optimism. Modernizing a data stack is often treated as a purely technical milestone, yet many projects fail despite perfect architecture. The premortem offers a psychological shift in strategy, moving

Trend Analysis: Generative AI Regulatory Oversight

The meteoric rise of generative artificial intelligence has fundamentally transformed the digital landscape, yet the initial period of unchecked experimentation is rapidly giving way to a strict era of federal oversight and rigorous legal accountability. This transition marks the definitive end of the “Wild West” period for machine learning, shifting the focus from speculative capability to demonstrable reliability. What was

Microsoft and Global Partners Dismantle Yam Store Phishing Network

The silent hum of a billion malicious messages flooding digital mailboxes across the globe finally met its match when an international coalition of tech giants and law enforcement agencies severed the digital arteries of the notorious Yam Store. This massive, industrial-scale “Phishing-as-a-Service” marketplace functioned as a centralized hub for cybercriminals, providing them with the sophisticated tools and stolen credentials necessary

ServiceNow AI Agent Governance – Review

The rapid transition of artificial intelligence from experimental side-projects to autonomous agents capable of independent action has introduced a profound governance crisis within the modern enterprise landscape. This evolution represents a shift from generative models that simply answer questions to agentic systems that execute complex workflows across disparate digital environments. ServiceNow has positioned itself at the center of this transformation,