It’s not just the tech — why culture is the hidden barrier to data success

You’ve got the talent and the tools. So why does your data still feel stuck? According to Confluent’s 2025 Data Streaming Report, if you feel like this, you’re not alone. 

In a survey of 4,175 global IT leaders, 79% say they face five or more data integration challenges.

But what’s telling is that these challenges aren’t only technical. They’re cultural. Fragmented ownership, siloed teams, and reluctance to share data are all blocking progress. 

This matters more than ever because real-time data streaming has become a business imperative. After adopting a data streaming platform (DSP), 84% report increased revenue, and 44% say they are seeing a return of 5x or more on their investment. 

Nearly nine in ten IT leaders now see DSPs as essential to achieving their data goals.

Yet for many, the full value of their data remains just out of reach because the culture isn’t ready.

The hidden barrier to data streaming success

Ask most businesses why their data investments aren’t paying off, and you’ll likely hear about technological gaps or complex architectures. But Confluent’s latest research suggests otherwise.

The report finds that 68% of IT leaders cite inconsistent data sources, 63% point to fragmented ownership, and 62% flag reluctance to share data across teams as persistent challenges. These are distinctly human hurdles.

Too often, organisations respond to data friction by adding more tech. But without a coordinated cultural shift, even the most advanced platforms may struggle to deliver impact.

What’s clear is that leaders must stop treating data streaming as solely a technology problem and start treating it as a transformation challenge.

Culture matters as much as compatibility

The 2025 Data Streaming Report maps out a clear maturity curve, from early experimentation through to enterprise-wide adoption. The research shows that two-thirds of organizations find themselves in the early to mid-stages, where streaming is confined to isolated systems or siloed teams.

In these environments, real-time data may be flowing technically — and the benefits starting to emerge — but it isn’t translating into sustained value. This is especially limiting for AI initiatives, which rely on consistent, trustworthy, and well-governed data to deliver real results. Without alignment across teams, AI efforts risk becoming disconnected pilots rather than scalable solutions.

Contrast that with the small group of high-maturity organizations that treat data differently. These leaders operationalize DSPs. They embed streaming into cross-functional workflows, supported by shared governance and reusable frameworks. And they foster a mindset where data is viewed as a shared enterprise asset, not a departmental resource.

Key to this is managing data streams as products, designed with clear ownership, documentation and long-term usability in mind. Rather than handing off responsibility from IT to the business and back again, teams are structured around domains such as ‘customer data’ and made up of diverse roles such as data engineers, product managers and analysts – together co-owning the quality, governance and performance of that stream.

It’s no surprise that 76% of IT leaders say data products help foster this kind of culture where data is scalable, reusable, and trusted across the business. What’s clear is that the path to streaming maturity isn’t paved with infrastructure upgrades alone. As the report puts it:

Real success — moving up the maturity curve — requires both the right tools and meaningful cultural and organizational changes.

A cultural commitment to trustworthy data

This mindset extends to how high-performing organisations design their data workflows, particularly through the adoption of ‘shift-left’ strategies. By embedding data quality, governance, and processing closer to the source, they reduce rework, lower costs, and ensure data is trusted and usable from the outset.

In practice, this could look like data engineers and software developers working together at the point of data creation, treating data pipelines with the same rigour as application code — including testing, versioning, and automated quality checks — while platform teams provide standardised, reusable templates for publishing data streams to ensure consistent formats and governance policies from day one.

The benefits are tangible. According to the report, 81% of IT leaders say shift-left approaches have helped reduce cost and risk. Ninety-three per cent report at least four significant advantages from a shift-left approach to data integration.

Shift-left isn’t just a process improvement. It’s a cultural decision to treat data as a critical business advantage from the very beginning.

The role of DSPs in enabling change

None of this is possible without data streaming platforms (DSPs). Far from passive platforms, DSPs act as the connective tissue of the modern enterprise, enabling data to flow securely and in real time across functions. They support embedded governance, enable data reuse, and provide the operational scaffolding to scale access without compromising control.

That’s why 91% of IT leaders say DSPs help break down data silos. Eighty-six per cent say they streamline access, and 80% credit them with improving governance. With this foundation in place, 73% say they’re better equipped to activate data for high-value use cases — from real-time customer insights to regulatory compliance to product innovation.

And when it comes to AI, DSPs are proving indispensable. By delivering enriched, high-quality data in motion, they allow organisations to build and scale AI systems with speed and confidence.

As Sudhakar Gopal, EVP & CIO at Citizens Bank, puts it:

Where would we be without a data streaming platform? I think we’d be out of business. A data streaming platform makes it easy for us to exchange data between all our point-to-point applications, enabling us to make game-changing decisions in real time.

Culture as the catalyst for data success

As the report makes clear, in the age of AI, real-time data reigns supreme. The technology is here. The ROI is proven. The strategic intent is understood. And as organizations move up the maturity curve, the benefits only compound.

What’s still missing for some is the cultural readiness to support it. The most successful leaders aren’t just investing in DSPs — they’re investing in shared ownership, reusable assets, upstream accountability, and cross-functional trust.

The future of data is streaming. Just make sure your people are coming with you.