FEATURE: DATA STORAGE AND DATA ARCHITECTURES
WE ARE SEEING STORAGE, COMPUTE, AND AI INFRASTRUCTURE MERGE, GIVING BUSINESSES A DIRECT PATH TO FASTER INSIGHTS AND BETTER PERFORMANCE.
Data management benefits from data fabric and AI classification, while real-time analytics speed decision-making. Availability rises with cloud-based backups and automated recovery, ensuring business continuity. New technologies like PCIe Gen5 and next-generation SSD form factors also deliver higher performance with smaller footprints, especially valuable for edge deployments.
“ For enterprises, data is either a competitive edge or a constant challenge; there is no in-between,” says NetApp’ s Issa.
“ Those who embrace modern data architectures gain speed and simplicity, freeing teams from tedious storage management tasks. AI takes care of optimisation, so businesses can focus on growth, not guesswork. With hybrid multi-cloud, data moves where it works best, cutting costs without compromising performance,” adds Issa.
Security is not a bolt-on it is built-in, protecting businesses from rising cyber threats. And as sustainability becomes a business mandate, energy-efficient storage ensures compliance without added complexity.
By prioritising intelligent data infrastructure, security, sustainability, and data unification, enterprises can navigate the complexities of AI and gain a competitive edge.
Enterprises that move to AI-ready data infrastructure gain more than speed, they gain a competitive edge. All-flash removes bottlenecks, enabling real-time AI, ML, and analytics. A disaggregated architecture not only reduces cost, complexity, and waste, but enables access to all manner of data previously locked away.
Scalability ensures growth without expensive forklift upgrades. Security and resilience protect critical data while meeting compliance. Faster insights mean smarter decisions. Software-driven automation slashes operational overhead.
Breaking free from legacy constraints lets businesses future-proof, optimise costs, and maximise data potential. The future belongs to those who build for it.
Challenges for building skill sets
Managing modern data storage and architectures is not just about being limited to technical knowledge. It must encompass adaptability, strategic thinking, and the ability to harness technology for business impact. Today’ s IT leaders need a deeper understanding of AI and automation, not just to implement them but to use them to reduce or eliminate complexity.
Multicloud expertise is critical; knowing how to move and manage data across hybrid and multicloud cloud environments without locking into one provider. At the same time, cyber resilience is no longer an IT issue; it is a business imperative, so security-first thinking is essential.
“ And with data volumes exploding, proficiency in analytics and unstructured data management ensures that storage is not just efficient but insightful. The real skills lie in bridging technology with business needs because the best storage strategies do not just manage data, they unlock value,” says NetApp’ s Issa.
“ Managing next-gen data infrastructure is not about hardware, it is about code and data intelligence. Teams need expertise in AI-driven storage, cloud integration, and software-defined systems. Understanding disaggregated architectures and optimising AI and ML workloads is key,” says VAST Data’ s Aziz.
Data engineering, security, and automation skills are essential. Kubernetes, multi-cloud, and containerised storage? Non-negotiable.
Strong problem-solving, scripting, and monitoring abilities are critical. As AI reshapes IT, professionals must be agile, data-first, and automation-driven. Expert tools like Terraform, Ansible, and data orchestration to get you to the front of the queue.
Professionals must master cloud and hybrid storage on AWS, Azure, and GCP, alongside data architecture and engineering covering data lakes, data mesh, and software-defined storage. AIdriven optimisation and automation skills enable efficient data management. Edge computing and IoT expertise are essential for real-time processing and distributed environments.
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