By all accounts, data democratisation sounds like a noble ambition: remove barriers to information, reduce dependencies, and allow anyone in the business to make informed decisions. But few understand the depth and discipline it takes to implement it responsibly.
For Henry Oribe, a senior data analyst whose work sits at the intersection of technical rigour and business impact, democratisation isn’t a one-off project, it’s an evolving system of trust, design, and accountability.
Over the years, Henry has observed a pattern common to many organisations. Business teams want to move faster, access data on their own, and reduce their reliance on centralised analytics teams.
Meanwhile, analysts worry about misinterpretation, duplication, and flawed conclusions. Striking the balance between autonomy and governance has become Henry’s central focus, and he’s done so by building what he calls “trustworthy independence.”
At the heart of this approach lies a shift, from analysts as gatekeepers of information to enablers of intelligence. This mindset change begins with the structure of the data ecosystem itself.
Henry doesn’t believe in handing over raw datasets to untrained hands. Instead, he focuses on designing semantic layers, human-readable representations of data definitions that abstract complexity without oversimplifying.
Tools like Looker and Power BI, when configured correctly, allow business users to navigate dashboards and run reports based on pre-defined metrics and dimensions, rather than writing SQL queries from scratch.
But giving access to tools is the easy part. What makes Henry’s approach effective is the architectural foundation that supports this access. Data catalogues play a critical role.
By documenting datasets, data lineage, ownership, and usage patterns, catalogues reduce the cognitive load on end-users and act as a safeguard against misuse.
In Henry’s recent projects, introducing Metabase’s integrated catalogue helped business teams distinguish between authoritative data and exploratory datasets, reducing duplicated work and inconsistencies in reporting.
Governance remains essential. Henry has led initiatives that implemented robust role-based access control (RBAC) systems, mapping access not just to organisational roles but also to specific use cases. For instance, a product manager might have visibility into product usage metrics but no access to personally identifiable customer information.
Finance teams, on the other hand, require deeper visibility into revenue flows but have no need to touch behavioural datasets.
By aligning access with need, Henry ensures compliance without throttling curiosity.
Training also plays a critical part in this transition. Rather than offering one-time workshops, Henry promotes ongoing collaboration between analysts and business stakeholders.
In practice, this means building “data circles”, monthly forums where users can review how they’ve used data to make decisions, surface challenges, and identify gaps in understanding.
In these sessions, analysts like Henry model how to frame better questions, critique flawed assumptions, and iterate toward better insights.
Henry’s philosophy mirrors the evolution seen at companies like Shopify and Airbnb. At Shopify, the move from centralised BI to a decentralised model involved creating a common language around metrics, what constitutes an active user, a churned customer, or a successful transaction.
Similarly, Airbnb built Minerva, an internal semantic layer that ensured consistent metric definitions across dashboards. Both companies saw measurable outcomes: reduced backlog for analytics teams, faster decision-making cycles, and improved business responsiveness.
Henry has brought this spirit into the organisations he’s served. In one instance, a marketing team that previously waited two weeks for insights began generating campaign reports within hours of launch.
But success isn’t just anecdotal. Henry measures impact through adoption metrics, how many users interact with dashboards, how frequently they return, and whether they act on the insights provided.
He also tracks downstream effects: are product strategies evolving based on usage data? Are customer support teams resolving issues faster with access to sentiment dashboards?
Notably, Henry does not advocate for unbounded freedom. Guardrails matter. He’s built alert systems that flag when dashboards are misconfigured or when KPIs deviate from expected ranges.
He’s integrated audit trails that show who made changes, when, and why. These controls don’t limit access, they reinforce accountability.
To Henry Oribe, data democratisation isn’t about letting go of control. It’s about building enough confidence in your systems and in your people to share ownership of insights.
It’s about elevating the questions people ask, not just the tools they use to find answers. And above all, it’s about designing with integrity, because true empowerment doesn’t come from access alone, but from understanding what to do with it.
