The lakehouse is a better data warehouse: 2026 benchmarks and proof
The warehouse was the right answer for 20 yearsThe data warehouse earned its place. For two decades...
The warehouse was the right answer for 20 yearsThe data warehouse earned its place. For two decades...
In context
- Topic: Datos y Analítica — Gobierno del dato, calidad, analítica y productos de datos.
- Source: Databricks
- Published: 06/10/2026
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Excerpt published automatically by the site radar. The full text belongs to its publisher and is linked above.
Why it matters
What gives data value is not having it, it is somebody changing a decision because of it. It sounds obvious and it is the test most projects fail: the report gets built, gets published, nobody changes anything, and six months later the project is recorded as a success because it shipped on time.
When I assess a data initiative, the first question is which concrete decision gets made with this and who makes it. If the answer is that it provides visibility, I already know the dashboard will be abandoned within a year. Visibility is not an objective, it is a side effect.
What usually goes wrong
What I see fail most is dashboard maintenance. It gets built carefully, used for three months, and then a business rule changes that nobody told the data team about. The number still comes out, it no longer means the same thing, and decisions keep being made on data that became false.
What to watch
- Whether definitions are agreed across areas or each one brings its own to the meeting.
- Where the data comes from and what happens when the source system changes or fails.
- When the number arrives relative to when the decision is taken, which is what defines its usefulness.
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.
This entry is an excerpt from the original source, selected by the site radar. The commentary above is the site's own and does not belong to the cited publisher.
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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.
