Future-proof IT environments with intelligent data management solutions
By Kate Mollett, Senior Regional Manager at Commvault, South and East Africa
In today’s data-driven economy, technology is at the forefront, with data being an organization’s most critical asset, giving it a competitive edge if used, leveraged and leveraged correctly. Data enables organizations to predict customer behavior, informs and directs business strategy, and can also help improve efficiency within the business.
Over the years, modern enterprises have witnessed multiple technological shifts in their day-to-day environments, moving from the era of the mainframe, to the era of cloud-based servers, to the virtual era, and then to embedded appliances. We are now in the era of microservices, containers and software as a service (SaaS), the latter of which are outright outpacing traditional applications.
While these new methods of innovation have brought great benefits to organizations – enabling them to adapt, become more agile and transform – they have also brought a set of significant challenges. Many of these environments have particular solutions that manage and protect them, resulting in pockets of data being protected in very different ways. Ultimately, this creates data silos within the environment, which are fragmented and very difficult to manage.
Managing a legacy environment with new evolving workloads entering the ecosystem is complex, and as the complexity increases, so does the security risk. As the security surface continues to evolve, the possibility of a significant data breach also increases. So, as organizations take advantage of this technological evolution, it is very important that they are aware of the security challenges that may arise.
For modern businesses to truly leverage their data as an asset, they must ensure that their data is available to all of their industries and other stakeholders so they can use it in meaningful ways. to have a competitive advantage. However, they also need to ensure that their security posture is rigid and robust enough to guard against data leaks and data breaches, which could negatively impact an organization financially and from a corporate perspective. reputation.
These challenges are not limited to IT, however, as digital transformation pushes organizations to depend on the integrity of their data. Therefore, for organizations to be able to make decisions, deliver microservices, and respond to market changes based on what the data tells them, they need to ensure that their data is flawless.
Main areas of risk
Unfortunately, the proliferation of data – the different islands and silos of data that are managed in different ways – introduces five main areas of risk:
- Data fragmentation and multiple points of failure – data is everywhere and managed to varying degrees and with varying degrees of success,
- Increased surface area for cyberattacks – data silos increase the attack surface, increasing the risk of cyberattacks,
- Regulatory and privacy requirements – organizations must ensure that sensitive and personal information is accessible, as a data leak could have significant consequences,
- The inability to scale and innovate – organizations are not leveraging their data in meaningful ways when in these different environments,
- Inability to introduce automation or operational efficiency – this cannot be done without having a good grasp of the data an organization has and where it resides.
So when we look at where many companies are today and where they need to go, we see a gap that we call the business integrity gap. To bridge this gap, organizations need to turn to a data management specialist who can deliver intelligent data management solutions.
Good data management technology is all about futureproofing an environment. Not only will this help organizations manage legacy data that is in the data plane, but it will also allow them to manage new datasets that come into the environment. This is especially important in the modern era, where every industry is driven by and dependent on technology.