BigDataLDN 2025. Less Noise. More Substance.

A week on from BigDataLDN and the dust (and confetti) has finally settled. Between the neon booths, robot dogs and endless ‘AI-powered’ slogans, one truth stood out: the data industry is maturing, but not fast enough.

We walked the floor, sat through the demos and listened to the buzzwords, so you don’t have to.

Here’s what actually mattered.

1. The Modern Data Stack Hangover is Real

There was a time when ‘modern’ meant something. Now it mostly means ‘complicated.’

Every aisle was filled with another orchestration tool promising to simplify the chaos, by adding more of it.

The new question isn’t ‘how do we scale our stack?’ It’s ‘why did we build one so complex in the first place?’

Most enterprise data pain isn’t technical. It’s organisational: misaligned priorities, disconnected teams, and over-engineered pipelines serving no clear outcome.

At Cloudaeon, we’ve seen this pattern across every large enterprise we work with. The winners are moving away from ‘more tools’ to fewer, better systems that deliver business value fast.

2. Databricks vs Snowflake: The Great Soap Opera Continues

No BigDataLDN would be complete without another round of platform theatre.

This year, the Databricks booth sat proudly centre stage, while Snowflake’s polar bear roamed the perimeter. Both sides claimed victory in the battle for the modern data platform.

The truth? Most enterprises don’t care who wins, they care who helps them deliver.

We run Databricks, Snowflake and Microsoft Fabric side by side across our client base and the story is always the same: success depends less on the platform and more on the people engineering it and the governance behind it.

3. AI Everywhere but Nowhere

If we had a pound for every ‘AI-powered’ banner, we could have bought the whole exhibition hall. From vector databases to ‘autonomous data quality bots,’ everyone claimed to have cracked the AI code. Few could show real outcomes.

AI isn’t a magic layer you sprinkle over broken data foundations.

It’s the next layer of dependency and fragility unless it’s built on governed, high-quality data. That’s why our focus remains where it should be: on the pipelines, the lineage and the logic that make AI useful rather than marketable.

4. Reality Check: Data ≠ Tech Problem

Jordan Tigani said it best: Big Data is dead, most workloads aren’t big, they’re just messy.

Scale isn’t the bottleneck anymore. Quality and understanding are.

The shift-left movement is right to focus upstream, define the goal, understand the process and measure what matters. That’s how we run every Cloudaeon engagement, from finance reporting to real-time ERP analytics.

Data problems have never been about tools. They’ve always been about people, process, and alignment.

Technology just exposes the cracks faster.

5. Our Takeaway: Keep it Real, Keep it Governed

Behind the mascots and marketing slogans, one quiet truth is emerging: the future belongs to those who can simplify.

Less hype. More governance. Less orchestration. More automation. Less ‘AI revolution.’ More measurable impact.

That’s the space Cloudaeon plays in building real, reliable data platforms that fuel insight and AI innovation without the noise.

So, while the industry debates its next acronym, we’ll keep doing what we do best:

Turning data into a competitive advantage, one governed pipeline at a time.