Hitachi Vantara: Helping Businesses Harness the Best of Data
Data has become one of the most valuable resources for businesses aiming to innovate, scale and compete.
However, unlocking its true potential requires more than just technology – it demands the right strategy, expertise and vision.
Dia Ali is Global Platforms & Solutions Leader for Data Intelligence at Hitachi Vantara. He has been at the forefront of helping global organisations modernise their data foundations, embrace hybrid cloud and adopt AI responsibly.
With a career spanning leadership roles at General Electric and Ford, Dia brings a unique blend of technical expertise and strategic insight to some of the most pressing challenges organisations face today.
At Hitachi Vantara, he focuses on data governance, hybrid cloud architecture and what he calls the AI Factory – a framework for building scalable and ethical AI systems that deliver long-term value.
As the digital innovation arm of Hitachi, Hitachi Vantara empowers businesses to modernise their infrastructure, accelerate data-driven strategies and unlock new opportunities with AI and advanced analytics.
From enterprise storage and hybrid cloud to data management and services, the company provides the foundations that fuel innovation worldwide.
Here, Dia discusses the future of data, cloud and AI with Technology Magazine.
What is edge computing and how does Hitachi use it?
Edge computing is a decentralised approach to processing data that enables computation to occur closer to the source of data generation.
This shift is crucial as the combination of cloud and edge computing paves the way for a new era of real-time intelligence.
Speed, intelligence and agility are no longer competitive advantages, they’re table stakes.
As data volumes grow – with the average large enterprise now managing 150 petabytes and expected to double by 2026, increasing the pressure for real-time responsiveness – edge computing is emerging as a vital shift in how enterprises build and operate their infrastructure.
According to Hitachi Vantara’s State of Data Infrastructure Global Report 2024, this surge in data is forcing organisations to rethink centralised architectures.
No longer confined to the margins of IT strategy, edge computing is being recognised as the core enabler of innovation across industries as wide-ranging as manufacturing, healthcare, banking and retail.
Why is proximity such a plus? The answer lies in the proverbial “distance from A to B.”
Data infrastructure teams now achieve unmatched speed and lower latency for essential operations through data processing that occurs near data origins.
The frictionless force multiplier provides organisations with real-time and actionable insights that drive operational optimisation and innovation.
The technology provides AI capabilities democratisation through its ability to perform advanced processing near the network’s edge, rather than requiring extensive deployments.
Hitachi Vantara supports this transition by enabling intelligent edge infrastructure that complements centralised systems and facilitates real-time insights and autonomy.
The limitations of conventional, centralised designs have been exposed by the explosion of real-time data.
Sending every byte to a central cloud server is becoming increasingly impractical. Edge computing solves this problem by bringing analytics and computation closer to the source, enabling localised action without requiring round-trip latency.
The bottom line is this: IT leaders looking to future-proof their organisations would be wise to move their computing operations toward the edge.
Is edge computing on the rise?
Massive investments are spurring this edge-adoption momentum.
IDC projects global spending on edge computing will grow at a compound annual growth rate of 13.8%, climbing to nearly US$380bn by 2028, up from US$261bn in 2025.
The numbers are staggering and there is no sign of this trend slowing down.
As IT executives seek to trim margins while optimising their data strategy, the demand for localised processing and analytics is expected to continue its growth spurt.
The business case for edge is no longer theoretical.
Delivery efficiency in logistics is increased when real-time routing decisions are made at the edge.
In the energy sector, edge intelligence-powered smart grids enhance load balancing and shorten outages. Public safety organisations implement edge-based video analytics to enhance their incident detection and response capabilities for a faster response time.
Together, these indicators confirm that edge computing is not only rising but rapidly becoming a strategic priority across sectors.
What is the relationship between AI and edge technologies?
The implementation of edge computing technology transforms the way artificial intelligence operates. Most AI workloads previously required extensive cloud infrastructure to operate.
AI functionality now operates at the edge due to improved computing and storage technology, creating new opportunities for applications that require low-bandwidth and low-latency operations.
From oil rigs and remote mines to rural healthcare clinics, organisations that embed AI into their edge operations are deriving insights locally and enabling autonomous decision-making where it matters most.
Consider manufacturing and production. AI models deployed on-site help plants detect irregularities and forecast maintenance requirements, leading to more seamless operational continuity.
Healthcare facilities leverage edge technology to deliver real-time patient monitoring via network bandwidth-independent methods.
Financial institutions are turning to edge computing to power faster fraud detection, enable real-time transaction approvals and deliver hyper-personalised customer experiences, all while meeting stringent regulatory and data residency requirements.
Edge computing makes AI more accessible and scalable by enabling real-time insights directly where data is generated.
How important is cybersecurity and compliance in modern edge computing?
Speed and insight matter, but without strong security and governance at the edge, they’re not enough.
Workload distribution does not need to compromise security measures.
Edge computing protects sensitive data through local processing that minimises exposure during data transfers.
Zero-trust architectures combined with data encryption and secure boot procedures have become standard practices that enhance the security of edge deployments by limiting access to authorised users, safeguarding data at rest and in transit and ensuring only verified software can run on edge devices – reducing the attack surface across distributed environments.
As an added advantage, edge models ensure that entities comply with local regulations and data sovereignty laws, particularly in regions with stringent guidelines on the use of personal data.
Security and compliance are foundational to successful edge deployment – not optional add-ons.
What does the future hold for edge computing?
Looking ahead, the real opportunity lies in fluid orchestration between edge and cloud environments.
Systems that facilitate the intelligent movement of workloads according to security, latency or regulatory requirements will provide the most significant ROI.
Forward-thinking organisations will embrace edge computing as a leap forward that complements – rather than replaces – centralised systems, enabling enterprises to act quickly, reduce risk and generate insights precisely where and when they're needed.
