Mindset Matters: A Successful Cloud Migration Starts with a New Way of Thinking

Ian Funnell, Director of Solution Architecture at Matillion, debunks some common misconceptions surrounding cloud migration.

In the 18 months where hybrid working has become an established part of everyday life, business continuity has been defined by the transition from on-premise to cloud computing.

It’s difficult to find businesses that think otherwise about the safety net that is the cloud, now that so much of the population conducts business operations from their own homes. Yet, many businesses are jeopardising their cloud success, and falling short of the ultimate goal of improved agility and efficiency, in their haste to adopt cloud data platforms.

Even now, organisations are still getting to grips with vast volumes of data and complex data sources. Despite the best intentions, many are leading with the misconception that  successful cloud migration depends solely on technology. Mindset isn’t always the first predictor of cloud success that comes to mind, in reality the success of a cloud transformation depends on the attitudes of an organisation’s IT leaders, and more importantly their willingness to adapt, as much as on the technologies they are investing in.

The bottom line is, if you want to change your organisation, you have to re-evaluate the role and value of technologies. This rings true for most digital transformations, but is especially true when driving organisational change through data analytics. With that in mind, I wanted to take this opportunity to debunk some common misconceptions surrounding cloud migration, and outlined what best practice looks like when it comes to altering an established cloud mindset.

From Output to Outcome-Focused

Many business leaders, struggling to move from a process-focused mentality to a data-focused one, are experiencing a disconnect in how to approach analytics. The main misconception is that simply copying data into the cloud is the quickest fix for solving integration and analytics problems. In fact, the key to unlocking scalability lies in moving storage and processing to the cloud, but it won’t generate insights if it’s kept in the same silos in a cloud environment. Such a process-centric view can lead to a proliferation of data that is collocated but not integrated.

Organisations need to think beyond “just get it into the cloud”, and take a more strategic, data-centric approach to the cloud transformation process. Shifting their view of technology from static to dynamic should allow IT leaders to derive more actionable insights that can elevate customer experiences, improve efficiencies, and better manage resources. Once we view data as a standalone, valuable entity instead of something that is simply a by-product of the work we undertake, organisations will begin to see change.

Technology isn’t the Be-All and End-All

Possessing the right data tools is mission-critical to a successful data migration strategy. There are hundreds of cloud data services to choose from, and IT leaders are persistently tasked with assessing the different functionalities on the market with the aim of finding the right solution from a sea of options.

Most are typically inclined to opt for the latest – but not necessarily the greatest – tools, assuming they will bring them business success. But much like with the confines of process-focused thinking, many come up short because they invest too much time trying to tap into the latest features, rather than focusing on the necessary requirements. Success shouldn’t be defined by brand reputation or price tag if the business is not making smart decisions with the resulting data.

Think about the emergence of low-code and no-code tools on the market. These technologies have disrupted the analytics space and changed it for the better, but by no means are they replacing data analysis and data engineering skills. Low-code empowers data analysts and data engineers with more time to focus on more complex matters. But low-code/no-code in a data silo won’t result in a differentiator for the business on its own. Their main value comes from alleviating otherwise burdensome tasks from data processing teams so they don’t become a bottleneck in the broader process.

Underestimating the Impact of Data

When different departments make different assumptions or apply conflicting standards, it’s likely that data quality will worsen more often than not. Many IT leaders are falling into this ‘decentralisation’ trap without realising it, because various business units within their business approach the cloud as a quick-fix, ‘off the shelf’ solution without considering how their data can be leveraged in other departments.

Instead of viewing cloud migration as a solution that will be most beneficial to the data team, IT leaders should take an enterprise-wide approach to digital transformation. Organisations that rethink data’s value proposition across the enterprise will not only eliminate the disconnect between teams during the transition to the cloud, but may also uncover additional value in the form of data insights that can be applied to other areas of the business.

The main takeaway here is data misconceptions are still holding organisations back from unlocking the kind of value they’re aiming for from cloud migrations. Yes, there are more technicalities that need to be addressed during this process which can be complex, but having a fluid, adaptable data mindset is critical and should be embedded across the enterprise before executing any specific data strategy. Taking a holistic view of cloud migration, in conjunction with this more informed approach to data, should allow businesses to sidestep some of the common pitfalls found in a cloud data journey, and ensure they derive the value that they’d hoped to realise.

By Ian Funnell, Director of Solution Architecture, Matillion.

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