The growth of data shows no sign of slowing down. In 2013, it was estimated that nine zettabytes of data were created, captured, copied, and consumed worldwide. Just a decade later, in 2023, that figure is forecasted to top 120 zettabytes – more than a 13-fold increase.

Today much of this data is spread across a variety of on-premise and cloud environments. However, this hybrid and often multi-cloud approach is introducing huge levels of complexity to organizations.

According to almost three-quarters (72 percent) of IT decision makers (ITDMs), having data sitting across multiple cloud and on-premise environments makes extracting value from it more complex.

In fact, the same research reveals that organizations are unable to use a third (33 percent) of their data effectively.

Imagine the business-critical information that could be sitting in that pool of untapped data. Those organizations that are able to drive value from all their data will be at a huge advantage compared to those that can’t.

Cloudy, with a chance of complexity

Clearly, the cloud has a role to play in an organization’s data management strategies. Today, many organizations have made the decision to go all-in on the cloud so that they can take advantage of the scalability it provides.

This shows little sign of slowing down, with 92 percent of ITDMs planning to migrate more of their data to the cloud over the next three years.

But 76 percent also have plans to repatriate some cloud data back to on-premise due to governance and compliance concerns – this issue is often more pronounced in EMEA than in the US due to where the major cloud providers are based.

Typically, workloads that are more predictable and consume a relatively stable level of resource are cheaper to run on-premise, whereas customer-facing services that are more variable in nature tend to be more suited to the elasticity of the cloud.

It is therefore hardly surprising that more than two-thirds (68 percent) of organizations currently store data in a hybrid environment – utilizing both public cloud, provided by the likes of AWS, Azure, and Google Cloud Platform, and their own on-premise data centers. 

Additionally, seven out of ten organizations currently have a multi-cloud model and are working with two or more hyperscalers.

Platform for success

Building a modern data architecture is critical for today’s organizations, enabling them to deliver vital insight from data regardless of where it resides. Data management platforms need to operate friction-free on-premises, across public clouds and the Edge, so that workloads and data can flow readily without the need for rewriting or refactoring.

The platform must also ensure that governance is always on, and everywhere. Finally, a platform must be able to handle all data types – structured, semi-structured, and unstructured; real-time, streaming, and batch.

With a solid data foundation, organizations will then be in a much better position to take the next step and apply tools such as machine learning and AI to it.

Getting true value from these potentially game-changing innovations is only possible if users are given access to organized, manageable, and complete sets of data, supported by the highest levels of governance and security.

Staying ahead of the data curve

At a time when all organizations want to move faster and are looking for benefits from AI, they need to stay ahead of the data curve. This means having the capability to securely extract value from their data regardless of where it resides.

But with the emergence of modern data architectures, organizations can drive more value from their data and optimize their cloud costs at the same time – which surely is a win-win.