Every product team wants to be data-driven. But what if the data they rely on is incomplete, delayed, or difficult to trust?
Data fragmentation, the splintering of information across dashboards, tools, and teams, is a major reason why product decisions often feel more like guesses than insights.
And it’s not rare. In fact, a 2023 survey by IDC found that 60% of organizations struggle to manage data spread across 10 or more systems. With each new source, it becomes harder to reconcile metrics or pinpoint the origin of a trend—let alone act on it confidently.
Why Teams Don’t Trust Their Metrics
When data is duplicated, filtered, or transformed through opaque processes, skepticism creeps in. Teams hesitate to act on metrics they don’t fully understand.
- Which version of the metric is correct?
- What methodology was used?
- Was the data delayed or filtered?
These are not edge cases: they’re everyday concerns. In a 2024 Deloitte survey, 55% of executives cited data trust as their biggest barrier to digital transformation.
The Visibility Gap Undermines Decisions
When key metrics stall or spike unexpectedly, fragmented systems make it nearly impossible to investigate the cause. This disconnect, what we call the data visibility gap, is the space between a company’s most important KPIs and its ability to understand them.
And it’s worsened by fragmented analytics:
- Metrics lack clear lineage or methodology
- Data lives in vendor dashboards outside your warehouse
- ETL pipelines introduce delays and transformation errors
- Teams lose confidence in the metrics they’re told to prioritize
Ultimately, product intuition suffers—and so does velocity.
What True Data Transparency Looks Like
Addressing broken trust in data isn’t just about improving workflow. It’s about restoring transparency, auditability, and governance across the organization.
Modern data platforms should provide:
- A single source of truth, directly connected to the warehouse
- The ability to see the SQL behind every report, ensuring clarity
- Role-based access controls for governance and security
- Consistent, trustworthy metrics across teams
According to McKinsey, organizations with high data transparency are 2.5x more likely to outperform their peers on key business metrics.
Gaining Confidence and Clarity in Your Analytics
Many analytics platforms require teams to extract, copy, or replicate data—introducing risk at every step. But there’s growing momentum behind warehouse-native analytics approaches that keep data exactly where it lives, reducing the need for duplication or transformation.
The result? Teams can see exactly where metrics come from, how they’re calculated, and what they mean—without delay or ambiguity.
In today’s fast-paced environment, data fragmentation is more than a technical headache—it’s a strategic liability. Without trust in the data, teams slow down, misalign, or revert to gut instinct.
By solving for transparency and governance, organizations can bridge the visibility gap and empower teams to move forward with clarity and confidence.
Because when teams trust their data, they trust their decisions
