The phrase “every business is a data business” may sound like a catchy buzzword, but it’s no longer just a trend—it’s a fundamental shift. In today’s world, every transaction, interaction, and process generates data. But merely having data is not enough. As Rory Yates, Global Strategic Lead at EIS, explains, “Data underpins everything. But that doesn’t make every business a data business.” He emphasises that organisations must understand how data drives business intelligence to gain a competitive edge.
Julian Browne, Chief Technology Officer, Modu says: “What does it really mean today to say, “Every business is a data business”? “All businesses are data businesses. The problem is that most don’t know it. As Marc Andreessen put it in 2011, “software is eating the world”.
And data is the fuel. Clearly, software has eaten the world. Seven of the world’s ten most valuable companies are tech businesses, and most of us work, bank, shop, create, travel, socialise and can even see a doctor via some form of app. So it follows that businesses embracing this fact will metamorphose into slick Silicon Valley-inspired data-driven engines of rapid product development. Yet many firms are like Peter Parker just after the spider bite: unaware of the great powers they already possess.”
We’re in the midst of an unprecedented data boom. According to some estimates, global data volumes will reach 181 zettabytes this year, with 90% of that data generated in just the last two years. And with the explosion of AI technologies, that growth will only accelerate. But here’s the catch: around 80% of this data is unstructured, buried in silos and legacy systems, making it incredibly difficult to use in a timely or meaningful way.
Massimo Merlo, Area VP for UK&I at Elastic, tells Silicon UK, “Collecting data isn’t enough. The real edge comes from turning it into insight—fast. Without context, data isn’t an asset. It’s just noise.” What separates leaders from laggards is not how much data they collect, but how quickly they can act on it.
Stuart Abbott, UK Director at VAST Data, adds another critical layer to this perspective. “Decisions are no longer made in boardrooms once a quarter,” he says. “They’re made by software, in real time, at scale.” In other words, data has moved from the background to the forefront of every business function, shaping everything from product development to customer service, in real time.
This means businesses that still see data as a backend utility or treat it like a compliance checkbox are falling behind. The modern enterprise needs to operationalise data across every touchpoint—not just store it, but make it accessible, searchable, trusted, and actionable.
Speed Means More Than Fast Systems
The concept of speed has evolved dramatically. In the age of instant gratification and real-time data, speed is no longer measured in how fast your systems process data. It’s about how quickly you can generate trusted, useful insights and apply them at the point of need.
Rory Yates recalls watching his father present on fibre optics decades ago. Even back then, studies showed it takes just four nanoseconds for the human brain to notice a delay—and from there, frustration builds. “To say we are an impatient species is an understatement,” he quips. Today, customers expect their data to follow them across devices, systems, and experiences without lag, disruption, or delay.
Massimo Merlo echoes this view: “Customers don’t measure speed in milliseconds. They measure it in outcomes.” Whether it’s resolving a complaint, receiving a recommendation, or seeing changes reflected instantly in a digital service, it all comes down to meeting expectations in the moment.
But speed without trust is a recipe for disaster. George Tziahanas, VP of Compliance at Archive360, explains that “the biggest differentiator is whether governance is treated as a brake or an accelerator.” Enterprises that integrate compliance into their data strategies from the outset are able to innovate faster, not slower.
VAST Data’s Stuart Abbott points out that speed is also about freshness. “You can have a fast query engine, but if it’s hitting an index that’s 12 hours old, it’s not helping anyone,” he explains. “Speed means fresh, trusted insight at the exact moment it’s needed.”
Ultimately, businesses must shift their understanding of speed from raw processing to real-time usefulness. That means tearing down silos, collapsing data layers, and investing in systems that bring analytics, governance, and access into a single fluid motion. Without this alignment, even the fastest systems won’t keep up with customer expectations.
Real Innovation is Built on Data Unification, Not Just Collection
With so much talk about AI, analytics, and digital transformation, it’s easy to forget a simple truth: if your data is fragmented, your insights will be too. The organisations that truly innovate are those that unify their data ecosystems, giving every stakeholder—from analysts to customer service agents—access to real-time, governed, and trustworthy information.
Take the example of HMCTS (His Majesty’s Courts and Tribunals Service). As explained in a case study from Through Technologies, the agency was burdened by dozens of siloed, outdated systems. It was slow, expensive, and impossible to innovate. By consolidating legacy systems into a single, governed archive, they unlocked accessibility and reduced risk, turning historical records into a strategic asset.
Massimo Merlo at Elastic notes that “every business problem is a data problem, and every data problem is, at its core, a pattern-matching problem.” That’s why search and discoverability are so crucial. If teams can’t find the data they need quickly, they can’t innovate.
Also, unification is about more than technical integration—it’s a cultural challenge too. Leaders must stop treating data as a technical resource limited to IT or analytics departments. As Merlo explains, “Leaders need to champion [data] as a shared organisational asset.” This shift from data as a service to data as a strategic utility allows businesses to move from isolated experimentation to continuous, enterprise-wide innovation.
And let’s not forget legacy data. Tziahanas tells Silicon UK that “archived and legacy data” are among the most untapped opportunities in enterprise AI. When governed properly, this data can power fraud detection, clinical research, and predictive planning—reducing time-to-insight from months to days.
So, if you’re building your data strategy solely around collecting more data, you’re missing the point. The future belongs to those who unify, contextualise, and act on their data in real time—and do so across the entire organisation.
Culture, Not Code, Defines Who Wins the Data Race
The final and perhaps most important factor in becoming a successful data business isn’t technology at all—it’s leadership culture. The way leaders think about data, communicate its value, and embed it into the company’s DNA determines whether innovation will flourish or fail.
“It’s still the most vital component in driving successful transformations,” emphasises Rory Yates. Too often, leaders focus on systems upgrades or analytics dashboards, but fail to explain why transformation is necessary, or how it will change the business fundamentally. That’s a problem.
Yates goes on to explain that businesses must move “from slow to fast, from policy-centric to customer-centric, from constrained to adaptive.” That shift can’t happen if leaders see data as someone else’s job. “Most people still see data as a specialism or career not relevant to them,” he says. “Leadership needs to be at the heart of driving this message home.”
Massimo Merlo agrees, saying that innovation comes from openness, experimentation, and a willingness to learn. He advocates for a leadership model that mirrors open-source principles: shared responsibility, rapid iteration, and a collective push forward. “Technology alone doesn’t drive change,” he says. “It’s the mindset and priorities set at the top.”
Stuart Abbott underscores the point: “The cultural shift isn’t about hiring a Chief AI Officer and hoping they fix everything. It’s about breaking down silos between data engineering, security, and business teams.”
In short, if leadership treats data as a static asset, the business will stagnate. If they treat it as a living system—accessible, adaptive, and central to strategy—they create the conditions for speed, scale, and long-term success.