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Articles on analytics engineering, data and artificial intelligence — no jargon, focused on business decisions.

IA & AutomaçãoJuly 15, 20262 min read

AI process automation: where to start (without an endless project)

Automating processes with AI sounds complex and expensive — but the best gains come from starting small, with a boring, repetitive process that steals hours from your team every week.

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BI & VisualizaçãoJuly 08, 20262 min read

Power BI vs Tableau vs Looker: which to choose (without the hype)

All three are great BI tools — and the "best" one depends less on technology and more on your context. An honest comparison so you can decide with judgment, not by trend.

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IA & AutomaçãoJuly 01, 20262 min read

AI agents for companies: use cases that pay off (and the ones that don’t)

Every company wants an AI agent, few know what for. The result is a flood of "pilots" that dazzle in the demo and die in a drawer. Let us separate what pays off from what is just hype.

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BI & VisualizaçãoJune 24, 20262 min read

How much does a Power BI dashboard cost? It depends on what it saves you

It is one of the first questions we hear — and a fair one. But the price of a dashboard tells you almost nothing without the other half of the math: what it gives back.

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Analytics EngineeringJune 17, 20262 min read

What is dbt? The tool that turned data transformation into real engineering

If you follow the data world, you have run into the acronym dbt. It shows up in job posts and in nearly every modern analytics project. But what does dbt actually do — and why did it become the standard?

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Estratégia de DadosJune 10, 20262 min read

How to build a data team (without hiring a whole department)

Your company has grown and now "needs a data team" — but building one from scratch feels expensive and risky. The good news: you can start with a business question and a clear roadmap, not a full payroll.

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Analytics EngineeringJune 03, 20263 min read

Analytics Engineering: the missing link between your data and your decisions

Your company has been collecting data for years, yet still decides on gut feeling? The problem is rarely a lack of data — it is the absence of a layer that turns it into something trustworthy. That is where analytics engineering comes in.

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