Analytics teams are moving faster than ever, using GenAI tools, spreadsheets, and whatever helps them get answers quickly. But when this happens outside of IT’s visibility — without approved tools or oversight — it creates shadow analytics. So the question is, how can organizations shine a little light and help point the path to a better way?
“We Just Needed to Get It Done”: Why Shadow Analytics Still Happens in 2025
First up, let’s take a step back and understand why this is still a problem. Let’s be honest, no one sets out to break rules. Most teams step outside official platforms because:
- It takes too long to get access.
- The approved tools are too rigid.
- They’re under pressure to deliver fast insights.
So, they find their own way — combining ChatGPT, Excel, slide decks, and shared folders. It works… until it doesn’t.
The result? Analytics workflows that IT can’t see, can’t secure, and can’t support. What organizations need is a balance point between control and flexibility — and that’s exactly what Dataiku provides. Let’s take a look at this from both sides.
What Analysts Really Want (and Why IT Needs to Listen)
I’ve been an analyst myself and I’ve worked with thousands over the last decade. And nine times out of ten, people aren’t trying to avoid governance — they just want to:
- Access the data they need.
- Work quickly without jumping through hoops.
- Leverage new tools like GenAI to speed things up.
- Share results confidently.
If the official tools block that? They’ll work around them. If a warehouse table isn’t accessible, they’ll find a colleague to email them an Excel export. If they can’t find that best practice example that already exists, they’ll whip up a new set of business logic from scratch. And if there isn’t an easy path towards leveraging GenAI to summarize customer care policies, they’ll upload them to a free chatbot service.
And that’s how shadow analytics grow when there isn’t a platform built that supports both speed and security.
What Happens When IT Loses Visibility
Now let’s take a second to understand why shadow analytics causes serious problems over time. When analytics happen outside IT’s visibility:
- No one knows what data was used (or if it was accurate).
- Teams duplicate work or come to different answers.
- Leadership starts asking: “Which number is right?”
- Critical data products can break with no easy way to fix them.
The crux of the issue is this: IT can’t do its job without some level of control. It can be difficult for an analyst to understand that the way insights are found and distributed can be just as important as the insights themselves.
Without quality checks, alerts, and deployment testing, that late night change made the day before a critical meeting can lead to a broken data product — leaving leadership without the numbers they need to make their pitch. Without one central location to track usage and maintain lineage, it becomes impossible to let analysts do self-service work at scale. The risk can actually vastly outweigh the opportunity of moving faster and leveraging domain expertise.
And over time it becomes harder to trust insights internally — and nearly impossible to prove them externally to auditors or regulators. The good news? Visibility doesn’t have to mean slowing teams down. Let’s look at a better way.
The Fix — A Better Way Forward With Dataiku
The crucial ingredient here is a platform where IT and analytics teams get what they need. In Dataiku:
- Analytics teams move fast — aided by GenAI and easy reuse.
- IT gets full visibility and control — through built-in governance tools.
- Everyone works in the same environment — no silos, no surprises.
Dataiku is The Universal AI Platform™ where IT can offer a controlled but powerful menu of analytic tools. This includes everything from curated datasets to forecasting templates to GenAI assistants backed with proactive budget controls. All projects, data, models, and logic are stored in a centralized, governed catalog, handy for an analyst looking to see what already exists and for IT looking to avoid sprawl and different calculations for the same KPI’s.
And this sets up a virtuous cycle: The easier it is to upskill and get work done, the more likely analysts will actually want to choose Dataiku. The added logging, permissions, and governance give IT the confidence to enable more compute, data, and analytics. Not to mention the giant jump in collaboration and scale that comes with avoiding legacy and desktop-based tools. Everybody wins!
Shadow Analytics Is a Symptom — Not the Root Problem
Shadow analytics is a sign that your teams aren’t being fully supported — and that your data workflows aren’t built for the way people actually work today. In 2025, analytics is more decentralized, AI-enabled, and fast-moving than ever. If governance can’t keep up, teams will inevitably go around it.
The answer isn’t just stricter controls, but a better foundation: A platform that allows IT to maintain control and security while enabling analysts to move at the speed of modern businesses today.
Dataiku provides IT and analytics teams a shared platform — one that’s secure, visible, and built to scale with GenAI. With the right platform, there’s no need for shadow analytics because the governed path is just as fast as unregulated alternatives.