A Databricks anunciou na semana passada seu plano de investir R$ 1,5 bilhão no Brasil ao longo dos próximos três anos, com o objetivo de apoiar a adoção de IA corporativa por meio do Lakebase, do Genie e do Unity Gateway. A empresa afirma que seus negócios no país quase triplicaram nos últimos dois anos, […]
A Databricks anunciou na semana passada seu plano de investir R$ 1,5 bilhão no Brasil ao longo dos próximos três anos, com o objetivo de apoiar a adoção de IA corporativa por meio do Lakebase, do Genie e do Unity Gateway. A empresa afirma que seus negócios no país quase triplicaram nos últimos dois anos, […]
Em contexto
- Tema: Datos y Analítica — Gobierno del dato, calidad, analítica y productos de datos.
- Fonte: CISO Advisor
- Publicado: 25/09/2026
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Why it matters
In data, the problem is almost never the tool. It is that two areas mean different things by customer and neither wants to give ground. You can install the most modern platform on the market and still have three sales figures in the same meeting.
I look at lineage before I look at the chart: where each number comes from, who can change it, and what happens if the source system goes down. If nobody can walk that chain in two minutes, the dashboard is displaying confidence it did not earn.
What usually goes wrong
Where it usually breaks is capture. A lot gets invested in processing and nothing at the point where a person fills in the form, in a hurry, with no validation and no idea what it is for. No model fixes data that was born wrong; it only propagates it with more authority.
What to watch
- When the number arrives relative to when the decision is taken, which is what defines its usefulness.
- Who answers for the quality of the indicator when somebody challenges it in a committee.
- Which concrete decision changes because of this and who makes it: without that, it is one more dashboard.
How I read this entry
I would use it to review the full cycle, from where the data is captured to where somebody acts. The problem is almost never in the analytics but at the start: someone filling a field by hand, with no validation, in a hurry, not knowing what it is used for later.
The original story is published in another language; the excerpt is quoted as the publisher delivers it and the commentary is written in English.
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Living through this in your own team?
Open the chat and tell me how you're handling it. I'm interested in comparing notes.
