Carl D ’ Halluin , CTO , Datadobi , tells us how businesses can balance scalability and security when managing large volumes of data in an increasingly complex regulatory landscape .

very business depends on data , and while it has

E become clichéd to claim it is

‘ the new oil ’, it increasingly serves as the fundamental foundation for decision-making and innovation .

Despite its importance , the approach organisations take to data varies dramatically . Many collect vast amounts of data without a clear vision of how it will be used and , instead , spend significant sums storing various datasets in anticipation of progress later on . Elsewhere , organisational leaders fully understand the latent potential in their data but lack the skills , processes or technologies to translate objectives into deliverables .

Get data strategy right , however , and businesses stand to gain enormous operational , financial and competitive advantages . But failing to capitalise can see organisations fall behind their rivals , with management coming under significant pressure to raise their game . All of this is taking place against the backdrop of a highly complex regulatory environment , where the scope for non-compliance is greater than ever . range of important priorities to balance if organisations are to build scalable , high-performance data environments that also deliver the high levels of security and compliance required . Let ’ s look at some of the key components in more detail :

1 . Establish a scalable data management framework

The first priority should be to implement a scalable data management framework . Why ? Well , up to 90 % of business data is now unstructured and can be anything from videos , images , scanned documents , and emails to social media posts and audio recordings , with data volumes growing at an exponential rate . As such , it lacks a predefined format and organisation , making it difficult to store and analyse in traditional databases .

For many businesses , this presents serious management challenges because , without the ability to organise , store and secure data to ensure its accuracy , accessibility and compliance , it becomes almost impossible to extract value . In these circumstances , any ambitions leaders have for their data assets will almost certainly remain unrealised .

Instead , organisations need clear insights into what data exists , where it resides , and how it can be used to enable better decision-making and governance . From a technology standpoint , these capabilities depend on vendor-neutral data storage and management solutions that ensure seamless integration across today ’ s hybrid IT environments . For example , AI-driven visibility and automation technologies are increasingly integrated with robust and

So , in the context of data management , what does ‘ good ’ look like ? There are a

www . intelligentfin . tech

67