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Companies have embarked on a digital transformation journey which entails embracing technologies such as Cloud Data Management, Artificial Intelligence (AI) and automation. But to do so effectively requires putting the fundamentals in place when it comes to data availability and business continuity.

According to the 2019 Veeam Cloud Data Management Report, forward-thinking organisations have four components in common: cloud; capabilities; culture; and confidence.

When it comes to the cloud, over three-quarters (77%) of respondents globally report using Software-as-a-Service (SaaS) platforms. Additionally, many are using the cloud for their backup and recovery services reflecting the business benefits of embracing a multi-cloud approach when it comes to data management.

In terms of capabilities, digitally-driven businesses understand the need to upskill employees and recognise that leadership styles also need to become more open and accepting. This leads in to creating a company culture that is adaptable and receptive to new technologies for the people, and the organisations themselves, to evolve as technologies change.

“Organisations must have confidence in their digital capabilities that grow as a result of having a strong data foundation. However, with only a quarter of respondents reporting total confidence in their abilities to meet digital transformation requirements, it is an area that still has significant room for improvement,” says Kate Mollett, regional manager for Africa at Veeam.

Clearly, this needs to change especially in a market where consumers and customers expect services to be always available – from shopping and banking to managing their insurance and medical aid. This has resulted in an inherent trust factor that ties all these elements together. And if that trust is broken, either by the unavailability of data or that data being compromised, customers will move to competitors who can deliver on that promise.

Managing data

“The traditional approach where availability is reliant on policy-based mechanisms and businesses having to manually relocate data to optimise cost and performance is no longer good enough. Digital transformation requires availability to be autonomous and proactive where systems react and adjust automatically to changes in the behaviour of data, apps, and users,” says Mollett.

Cloud Data Management becomes critical in the transition to a more digitally-enabled environment. Fundamentally, this sees a shift from policy-based to behaviour-based solutions in a journey that spans five stages (backup; cloud mobility; visibility; orchestration; and automation).

Backup ensures that all organisational data is protected, replicated, and recoverable. This is the cornerstone as data outages, attacks, loss, or theft can significantly and negatively impact the success of the business. Once the appropriate measures are put in place, the business can start exploring cloud-based solutions to supplement its baseline activities. The second stage (cloud mobility) sees organisations backup and moving their data to, from, and within various cloud environments. This revolves around creating a more agile and mobile business capable of accessing mission-critical data regardless of device used or the physical location of employees.

The third stage (visibility) enables the organisation to have a full view of its data as well as the infrastructure required to manage it. Without the required insights to identify where the management can improve, the digital transformation journey can likely stagnate or veer into the wrong direction.

“This visibility guides decision-makers into the next part of their cloud journey. It is therefore critical to ensure it is done right and provides the right analysis for the company to improve its data service level agreements (SLAs) while lowering costs,” says Mollett.

Digital autonomy

Stage 4 (orchestration) marries the best of technology with the best of human insights. It ensures the consistent execution of complex tasks and improving the manageability by reducing burdensome tasks and optimising workflow inside the organisation.

This stage ensures the data availability measures are tested, optimised, and executed with the best possible chance for success. Managing this process ensures IT teams are less focusing on maintenance and support, and more focused on delivering strategic value to the business.

The final stage (automation) is where data becomes self-managing by learning how best to protect itself with the SLAs, methods, and locations required to best meet the objectives of the company. This is where the likes of IT-as-a-Service comes in where the underlying infrastructure operates as transparently as possible to the users.

“Data management must be engrained into all facets of the organisation if it is to become digitally transformed. The will to change must be there and the phased approach becomes indispensable to continually evaluate and enhance the data journey for the business,” concludes Mollett.