The transition from on-premise to cloud computing is inevitable
You would be hard-pressed to find a business that disagrees with this notion, especially since the pandemic accelerated hybrid working for many. However, in the haste to adopt cloud data platforms, many businesses have failed to meet the ultimate goal of improved business agility and efficiency.
Getting a handle on the increasing volumes of data and multiple data sources is still a new and challenging concept for many organisations, so despite the best intentions, the reality is often still one of missed opportunities. One of the key challenges is that business leaders believe that successful cloud migration depends solely on technology. While technology is important, the reality is that this transition depends on an organisation’s IT leaders and the mindset they have when approaching today’s complex data environment.
If you want to change your organisation, you have to change your viewpoint on how things are typically done. This is true for most aspects of business, and it is certainly true for how we approach driving organisational change from data analytics. To do so, we’ve collated some of the most common data misconceptions when it comes to cloud migration, and what best practice looks like.
Process Focused vs. Data Focused
There’s a massive disconnect in today’s organisations about how to approach analytics. Many business leaders are stuck in a process-focused mentality. The main misconception is that simply copying data into the cloud can immediately solve integration and analytics problems. Of course, moving storage and processing to the cloud is a prerequisite to unlocking scalability. But on its own, it doesn’t generate insights. On the contrary, such a process-centric view can lead to a proliferation of data that is collocated but not integrated.
We need to move beyond the “just get it into the cloud” mindset. By taking a more strategic, data-centric approach to the cloud analytics process, IT leaders will be able to drive more actionable insights that can be applied to the business to improve customer experiences, contain costs, and better manage resources. Once we begin to treat data as a standalone, valuable entity instead of something that is simply spat out of a process, things will begin to change.
Technology as the Be-All and End-All
Let’s be clear. The right data tools are absolutely important to a successful data migration strategy and IT leaders need to do their due diligence to find the right solution. With hundreds of cloud data services to choose from, it’s necessary to evaluate the different functionalities that they provide. However, the underlying problem is that some hold the belief that the latest and greatest tools are what will ultimately bring them success and make the most impact on business.
Similar to being overly process-focused rather than data-focused, today’s organisations can be caught out by just trying to acquire the latest feature sets, rather than focusing on their requirements. The most powerful tool on the market won’t guarantee success if the business is not making smart decisions with the resulting data.
A prime example of this is the emergence of low-code and no-code tools on the market. These have drastically changed the analytics space, and for the better. However, we need to clear up the misconception that these tools are replacing data analysis and data engineering skills. Low code is useful because it enables data analysts and data engineers to focus their efforts where they are most valuable. But low-code/no-code on its own is not what’s going to create differentiators for the business. Low code is a prerequisite piece of the puzzle, but the main value is to alleviate some of the burdensome, time-consuming tasks so they don’t hold up the analytics process.
Narrow-Minded View of Data’s Impact
Data quality can suffer as a consequence of decentralisation, for example when different departments make different assumptions or apply diverging standards. Yet many IT leaders are falling into this approach without realising it. Much too often, teams approach the cloud as a quick-fix solution but fail to consider how their data relates to other departments in the business.
Instead of viewing cloud migration as a data-team-specific solution, IT leaders should approach this process as a means to enterprise-wide digital transformation. By taking this into consideration, organisations will not only avoid a massive disconnect during this transition but may also uncover some unexpected value that these data insights can provide to other areas of the business.
The bottom line is that those who fail to derive true business value from cloud migrations are typically holding onto some common data misconceptions. While there are certainly more technical factors that need to be addressed during this process, having the right data mindset is foundational and should first be addressed before executing any specific strategy. Viewing any migration in a more holistic manner will set businesses up for success and avoid some of the common pitfalls that IT leaders face on their cloud data journey.
About the Author
Ian Funnell is manager of developer relations at Matillion, helping to empower the developer community to get the best out of Matillion in the quest to maximise the value of their data. He has 25 years of experience in data architecture, data modeling and data warehousing.
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