Companies and organisations will usually handle this landscape in a divide-and-conquer-like manner, breaking large chunks of data down into smaller, more-manageable tasks and then solving these tasks with domain-specific techniques. This is why in enterprise IT- for example- you often see businesses embracing specialised technologies to solve particular problems, leading to multiple silos of data in the organisation.
However, this strategy can often end up being unproductive and even disruptive, with data integration across multiple sources becoming a challenge for users and a critical issue for the wider organisation...
Untangling the patchwork of complex IT stacks
In enterprise IT, a whole new set of technologies has taken the field by storm in the last few years: Big Data/ Hadoop/ Spark systems, document-oriented databases, graph databases, streaming data processing, search engines, in-memory grids. The list goes on...
And these technological innovations and trends are opening up a whole new world of possibilities. In theory, businesses should be able to utilise their data to progress further digitally than ever before. They are also the reason why many organisations have made a move away from old-school “one-size-fits-all” platforms, instead choosing to embrace specialised technologies that can solve specific problems.
Yet, whilst specialisation is arguably the way to go when it comes to dealing with very specific and complex business needs, it can also create its own problems- especially when it comes to giving users fast, real-time access to the data that they need to make the best decisions for the organisation.
Too often, specialisation will transform IT stacks into a patchwork of new technologies and data silos that then become difficult to integrate and- therefore- manage. This, in turn, makes it frustratingly difficult to consume data effectively across the organisation.
What was the solution, becomes a huge problem.
When is data integration a critical issue?
When different business units are using different technologies and moving in different directions, data integration can soon become a critical issue across the organisation. This usually manifests itself in the following ways:
·Multiple data silos – With data spread across numerous stores, often in different formats and with different interfaces, organisations are forced to spend considerable time, effort and money replicating it. Otherwise there’s no way to realise value.
·A growing need for highly specialised and specific skills – As technology diversifies very specific skillsets are needed, which rapidly becomes costly and inflexible for organisations.
·Difficulties in securing data enterprise-wide – With different systems varying in terms of digital security, metadata management and policies, it’s very difficult for organisations to ensure that they are 100% protected and compliant.
Add to this the creation of diverse ecosystems, which many traditional data integration technologies struggle to deal with, and it’s undeniable that IT teams face a complex problem.
And it’s no longer just the IT team. In fact, long gone are the days when this was purely an ‘IT problem’. Instead it is now a business-critical issue because data- whether it’s being collected or analysed - is what drives the digital enterprise.
Data virtualisation solves IT complexity issues
So, what’s the answer to this business-wide issue?
...Enter, data virtualisation.
Next generation solutions- like the Denodo Platform- are able to address the above types of data integration needs by offering the organisation a unified data access layer, removing the need for specialised IT skills and helping to centralise data governance and security.
This way, enterprises can continue to adopt best-of-breed specialized technologies, and at the same time, better manage them using data virtualisation.
It helps to deal with the issues thrown up by increasing technological and data complexity across the organisation whilst enabling organisations to keep up with their competitors. In other words, it enables organisations to have the best of both worlds.
Above all, data virtualisation is a solid strategy for delivering the data that matters to the people that need it, whenever, wherever and in real-time.