Modernising your data platform sounds simple enough: retire the spreadsheets, plug in a new cloud platform, and watch insights flow.
The reality is more complicated. Many organisations invest heavily in technology only to find adoption is low, costs keep climbing, and the return on investment never arrives.
The good news? Most of these challenges follow the same predictable patterns. Here are the five most common pitfalls of data platform modernisation and how to avoid them.
Pitfall 1: Tech ≠ Value
A new platform does not automatically create business impact. Starting with Microsoft Fabric, Snowflake, or Databricks before defining outcomes is like buying gym gear and never working out. You end up with great tools that no one uses.
How to avoid it: Anchor the project to business goals. Ask which decisions need to be faster, safer, or smarter, then design the platform around those outcomes.
💡 Example: In our Modernising a Cloud Data Platform case study, aligning technology to business outcomes helped a client reduce costs, improve governance, and deliver real-time insights through Microsoft Fabric.
Pitfall 2: Nobody Uses It
The platform launches with excitement, training runs once, and within weeks everyone is back in Excel. Suddenly, your new system becomes the world’s most expensive filing cabinet.
How to avoid it: Treat adoption as part of the build. Create dashboards that solve real business problems, keep training ongoing, and focus on lifting data literacy so teams feel confident using the tools.
💡 Example: In our Unlocking the Full Value of Microsoft Fabric case study, continuous training and diagnostics helped stabilise reporting and turn a low-adoption platform into a daily business essential.
Pitfall 3: Forgetting Governance
Governance often gets pushed to phase two in the rush for quick wins. The result is a platform full of data that no one trusts. Without trust, people avoid using it and the cycle repeats.
How to avoid it: Embed governance from the start. Define ownership, rules, lineage, and quality controls early so data is reliable and decisions can be made with confidence.
💡 Example: In our blog Data Governance Isn’t a Sprint, But It Doesn’t Have to Be a Marathon Either, we show how early, lightweight governance can set the foundation for lasting trust.
Pitfall 4: Trying to Do Everything at Once
Ambition is good, but building the perfect platform in one go is a recipe for delays, ballooning budgets, and lost stakeholder confidence. The boil-the-ocean approach kills ROI before it starts.
How to avoid it: Deliver in iterations. Start with one high-impact use case, prove value, then expand. Small wins build momentum and show the business why the investment matters.
💡 Example: Our Modernising a Cloud Data Platform case study shows how one organisation proved value with a single high-impact use case before scaling. This approach reduced risk while accelerating ROI.
Pitfall 5: Ignoring AI Readiness
Everyone wants AI, but if your foundations are messy, AI only amplifies the problems. Garbage in means garbage out at scale.
How to avoid it: Build a unified, trusted platform first, then introduce AI where it adds measurable value. Focus on strengthening your foundations now so AI is an accelerator rather than an expensive experiment.
💡 Example: In The Brutal Truth About AI ROI (That No One Wants to Admit), Ben Winterbourne explains why most organisations struggle to see returns on AI investments and how strong data foundations turn hype into measurable value.
Why these pitfalls matter
Data modernisation is not about ticking the “we are on Fabric” or “we have Snowflake” box. It is about building a modern data platform that delivers faster insights, trusted data, and an AI-ready foundation.
Avoiding these five pitfalls helps your organisation:
- Reduce wasted spend and delays
- Accelerate ROI
- Build trust in data
- Lay the groundwork for AI adoption
Platform modernisation is a journey, not a destination. Keep reviewing, refining, and realigning your platform as your organisation evolves.
Want to know where you stand?
Most organisations fall into at least one of these traps without realising it. That is why we created the Data Platform Readiness Assessment.
It is a free session where our experts evaluate your current data environment across:
✅Technology and architecture
✅Governance and trust
✅People and adoption
✅Cost alignment and ROI
You will receive a tailored readiness scorecard and practical next steps to modernise with confidence.
Book in here: Data Platform Readiness Assessment.
Platform Modernisation FAQs
What is data platform modernisation?
Upgrading legacy data systems to a unified, cloud-based platform that delivers faster, more reliable insights and supports AI innovation.
Why do most modernisation projects fail?
Because they focus on technology over outcomes, skip governance, and neglect user adoption.
How can success be measured?
Track user adoption, cost savings, and decision-making speed to see real business impact.
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