FEATURE DATA MANAGEMENT

ver the years, the grand contours of data and data management have evolved constantly, to provide new ways of addressing an ever changing set of requirements.

From relational databases to data warehouses, data lakes and now lakehouses, structured or unstructured data, in various formats, on-premises or in the public cloud, and accessible via many different protocols, the result for many organisations is that they have dozens of ways to manage and address data to support all their applications, business units and populations of users.

The introduction of strict data regulations as well as a greater focus on data resiliency, security and governance mean that analysing and operationalising this data, while complying with regulatory requirements and internal policies, has become a very complex task.

This is compounded by the rise of AI in the Enterprise, which not only requires access to data in all its forms in order to deliver its promises, but also generates its own data that needs to be understood, stored and secured.

Siloed storage is inefficient, vulnerable and costly

How does data storage fit in? In many large organisations, on-premises storage arrays are still dedicated to vertical application stacks, not just isolated but also managed independently on an array-by-array basis.

There are generally very good reasons for this mode of operations, which could be technical or organisational. The result however, is fragmentation and silos of data and management which is not only inefficient and costly( as it can often lead to under-utilisation) but can also hinder the access to or the movement of data.

This creates a situation in which the data footprint grows, and at the same time becomes increasingly inaccessible, harder to manage, and more vulnerable to compliance risk and cyber-threats. That’ s because, as data is attached to particular applications, it becomes captive with no way to access it other than via its native application, or to copy it and move it.

Developers, data scientists and users need to work on datasets as they build and re-work applications, run reports and analytics etc. in real time. Without being able to work on them in one place, they copy data to a convenient location. That’ s a common practice that takes data beyond the reach of other applications and beyond best practice governance. The result is multiple exposed copies over which the organisation loses visibility and control, lacking the necessary governance and protection.

If an application, other than the one for which the storage array and its volumes

As data volumes and complexity continue to rise, organisations are seeking smarter, more unified ways to manage storage, governance and scalability across hybrid environments. Fred Lherault, Field CTO, EMEA / Emerging, Pure Storage, tells us how the Enterprise Data Cloud enables policy-driven automation, intelligent insights and seamless scalability to simplify operations and future-proof data management.

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