Getting your data science code running anywhere The post Deploying Data Science Tools: Part 1 appeared first on Towards Data Science.
Getting your data science code running anywhere The post Deploying Data Science Tools: Part 1 appeared first on Towards Data Science.
In context
- Topic: Datos y Analítica — Gobierno del dato, calidad, analítica y productos de datos.
- Source: Towards Data Science
- Published: 16/10/2026
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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
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.
My criterion is that data only helps if it arrives in time for the decision it is meant to support. A perfect report that lands on the eighth for a decision taken on the third is a useless report, however correct it is. Timeliness beats precision more often than people admit.
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
- 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.
Comments
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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.
