Data virtualisation – the missing link in cloud migration

Over the years, cloud computing has shifted away from being an optional part of a wider business strategy. It’s now seen by many as a necessity; a way of life.

Thanks to the promise of increased agility, flexibility and scalability, many have already joined the wave of cloud adopters currently sweeping the business landscape. Yet, despite recent reports predicting that cloud specific spending is expected to grow at more than six times the rate of general IT spending through 2020, the reality is that the majority of organisations have yet to reach the advanced stages of cloud implementation.

Whether it’s challenges with moving existing data to the cloud, security, worries about cost or a lack of adequately trained employees, something is standing in the way and – as a result – many are failing to reap the full benefits associated with transitioning to cloud.

This is where data virtualisation can help.

The missing link

By developing a single, logical view of all the data a business possesses, data virtualisation enables uniform access to all information, regardless of where it is being stored. It allows the creation of a virtual infrastructure – spanning both on-premise and cloud environments. This, in turn, helps businesses to overcome connectivity, security and compliance challenges and feel more confident about keeping data in a cloud environment.

In essence, data virtualisation simplifies the whole cloud process; empowering businesses and enabling them to go one step further when it comes to cloud migration.

For example, one of the first cloud-related challenges that organisations come up against will often occur in the migration stages. Moving data from an on-premises repository into a cloud one is no easy feat.

This is, in part, due to businesses needing to be able to migrate their data to the cloud without affecting their existing applications. Data virtualisation solves this issue by decoupling the data consumers from the underlying technical infrastructure, allowing for a seamless transition. Without this, organisations could risk impacting overall business productivity and even downtime, both during and following the migration period.

Another big challenge is how to integrate the new cloud systems with the data sources which inevitably will remain on-premise, at least for some time. By generating a logical overview of all enterprise data, without having to duplicate information in a physical repository, data virtualisation enables organisations to save businesses time, money and resources.

The promised land for big data analytics 

For many businesses, cloud computing is seen as a tool which will enable them to remain relevant to their customers and gain the competitive edge. This is never truer than when thinking about it in the context of big data analytics.

By using big data analytics in the cloud, businesses can analyse larger amounts of data – both structured and unstructured – than ever before. This can help them to monitor business trends and glean a fuller picture of what is happening throughout the entire organisation; insights which can then be used to drive productivity and inform key business decisions.

But, for many organisations, relocating big data into a cloud environment can be a cause for concern, especially when it comes to security and governance. This is because big data will often incorporate sensitive information, such as the personal details of individuals working within an organisation or even the customers that they interact with each day. This data needs to be carefully managed so users get access only to the pieces of data they are authorised to see.

With GDPR and other regulatory legislations coming into force, the potential risks of not fully protecting this type of data could be substantial for any businesses, regardless of size or sector. The initial fines – followed by the long-standing reputational damage – that a business in violation of GDPR will face could be enough to destroy its entire brand beyond repair.

In addition, to ensure data quality it’s also crucial to guarantee that the data delivered to the users of the analytics initiatives complies with the formats and rules defined by global governance policies.

It’s no wonder that moving big data to the cloud can be somewhat intimidating! The fear, alongside the sense of a loss of control, so often associated with migrating to a cloud environment can make it difficult to get everyone on board. It can feel almost like taking a leap of faith into the unknown.

However, data virtualisation can help to calm these fears and put minds at ease. By integrating all enterprise data across various disparate systems, it helps to create a centralised security and governance data delivery infrastructure. This provides businesses with a single point from which they can apply security and governance policies and rules across all data, whether it is being stored in the cloud or on premise. This is the basis for providing a ‘single source of truth’ for data consumers, while guaranteeing security across all locations.

 Optimising cloud migration

Although migrating to cloud is no longer a ‘new’ concept, many businesses are still failing to reap the rewards in full.

Data virtualisation is changing this, enabling organisations to enter into the world of cloud at full speed. By providing a single, logical view of all data no matter where it resides, data virtualisation is opening the door for all businesses, helping them to migrate data smoothly and diminish any security or compliance fears.

Data virtualisation is opening a new chapter in cloud migration, full of opportunity for those organisations looking to stand out from the crowd and gain a competitive edge.