Why do enterprise data platforms projects so often hinge on a single “but”? When a user says, “I love the dashboards, but…”, you know the uncomfortable truth about user adoption is right around the corner.
“I love the dashboards, Andy, but can’t we plug in something like a ChatGPT on top of them, so I don’t have to interpret the data? I could simply chat and get my answers.”
It wasn’t meant as an insult to my years in data engineering and dashboarding. Yet, seeing the CMO of a US fashion apparel brand not keen on visual exploration bothered me deeply.
Why Marketing and Operations Leaders Need Different Enterprise Data Platforms
Cut to a different scene, where I found myself facing a young manufacturing CEO. Lauren* had recently taken the reins from her father and was remarkably fluent in the language of IT. It was a pleasant surprise, considering most manufacturers I knew were brilliant domain experts but easily overwhelmed by tech. As Lauren scrutinized the custom-made enterprise data platforms, I quickly disclaimed that a chat-like AI assistant is already on our roadmap.
She nodded, but was already digging into the dashboards. She drilled up and down like a seasoned data analyst, slicing through different charts and even setting up a custom view that mapped the operator productivity across supervisors.
That was my moment of reckoning. I couldn’t help but contrast the two leaders. The marketing leader was a storyteller at heart, for whom flashy bar charts or hover tooltips were just cognitive overload. She needed a natural language AI assistant. On the other hand, the manufacturing CEO was a woman of few words. The dashboards perfectly served her analytical mind.
Pondering over these two starkly different personalities, I can’t help but wonder how data engineering services firms acrosss the US business landscape spend weeks crafting modern data platform architectures– encompassing robust data pipelines, governed data lakehouses, and real-time dashboard insights. Yet enterprise data platforms often fail not because of engineering constraints or tech resistance. It’s because the design overlooks the user persona.
Why Do Operational Teams Prefer AI Autonomous Agents Over Enterprise Data Dashboards ?
Let me illustrate a third persona we encountered during a Tableau to Power BI migration for Luminotrix* – a midmarket US laser tool manufacturer. The company had used an on-premise Tableau version since its inception but when they grew, the per-user Tableau costs began to rise. An underutilized M365 license sparked the Power BI migration, projecting a healthy savings of more than 30%. However, certain users were accustomed to Tableau’s inherent visual sophistication. To bridge the gap, Trigent replicated 14 Tableau features in Power BI including floating layouts, customizable tooltips and the live-query experience.
During the post migration user feedback, the CIO caught us completely off-guard. “You got the data platform layer right. But I think some of our users don’t have to use Power BI at all.” On the surface, his observation pointed to Power BI’s native integration with Excel, where users can directly analyze data while using the governed data model from Power BI.
But the CIO was actually referring to the fact that the busy plant managers had zero time to probe numbers or talk to AI assistants. They might instead need autonomous agents that monitor anomalies, alert when exceptions arise, and recommend the best course of action. Don’t be surprised if this persona is not logging into your dashboards. They don’t want to explore data – they just watch out for alerts and precisely follow the agent instructions.
What Are the Core User Personas of an Enterprise Data Platforms ?
The below table sums up the priorities of these user personas
| Narrative Seekers | Data Lovers | Action Takers | |
|---|---|---|---|
| Expectations on data platform | Precise contextual answers | Metrics and visualizations that help discover insights | Agents to instruct the next course of action |
| Mindset | Let’s chat and figure this out | Let me find my way out through drill-ins and drill-outs | Just tell me what to do |
| Relationship with data | No, I can’t interpret it | I love numbers | I don’t want to see data |
| Preferred interaction | Natural language | Interactive dashboards | Recommendations and alerts |
| Success metric | Fast answers | Rich visualizations | Better decisions |
You may have heard experts and novices alike proclaim that dashboards are dead, but those conclusions were often drawn with only one user persona in mind: the marketing leader who would rather converse with an AI assistant than explore charts. But what about the young manufacturing CEO who loves granular insight? Lauren* believes that a single centralized dashboard ensures that no critical issue slips through the cracks. She even confessed that she opens his dashboard every morning before reading her emails. Then there is the third persona: the plant manager who might not be glued to your dashboard, but relies on agentic alerts to navigate daily operational decisions.
The success of enterprise data platforms invariably rests in the hands of these distinct user personas and once their unique needs are catered to, there are no ifs and buts. Your dashboards are truly loved.
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