At T-Mobile, our Power BI team could build any chart or visualization you asked for. Brilliant coders who loved data. However, they had no idea what the data actually meant.

For example, they’d build a dashboard showing network incident trends by region. Beautiful color gradients. Interactive filters. On the surface, it looked polished. Yet the colors didn’t match operational reality. The metrics weren’t what leadership cared about. The views were organized the way a developer would arrange data, not how a Senior Director would consume a morning briefing.

That’s where I came in.

Most of the time, I reviewed the output and asked the questions that mattered. What does this mean for the network? Which metric should leadership focus on first? How should this be organized so someone with 30 seconds between meetings can see what they need? Occasionally, I’d write a Power BI query myself or edit one to pull the right data. But my real value wasn’t the code. It was knowing what the code was supposed to produce.

The result was dashboards that actually drove decisions. Not because the technical work improved, but because the data was interpreted by someone who understood the operational context behind it.

That skill is easy to overlook, yet incredibly valuable in any organization. The person who translates between data engineers and decision-makers — who can look at a raw metric and tell you whether it’s a problem, a trend, or noise — that person makes the entire team more effective.

So if you’re building dashboards for an engineering or operations team, don’t just ask “what data do we have?” Instead, ask “what decision does this data need to support?” Then find someone who understands the domain to help answer that question.

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This is the first of what I hope to be several posts about the intersection of telecom engineering, data visualization, and operational excellence.