About data.day
data.day is a practical editorial experiment for people who do the work that keeps the business running.
Not the glamorous work. The real work.
The “why doesn’t this number match?” work. The late export. The broken dashboard. The pipeline that fails at 02:11. The definition that changes mid-quarter. The spreadsheet that becomes a system because the CEO needs an answer tomorrow.
Most organizations run on that work. Most organizations also pretend it does not exist.
So we write about it.
What we publish
We publish practical articles on data work: how to structure datasets, how to keep pipelines reliable, how to build metrics that survive scrutiny, and how to deliver numbers without creating chaos.
Expect checklists, templates, and patterns we can reuse. Expect strong opinions about discipline: definitions, constraints, provenance, and clarity. Expect fewer vendor fairy tales.
What we are not
We are not a magazine. We are not a trend site. We are not a vendor blog. We are definitely not a glossy publication.
We do not do sponsored “thought leadership.” We do not write to impress. We write to be useful.
The collective
data.day is written by a small collective of practitioners who vaguely know each other through projects, referrals, and the broader European data scene.
We write under fictional pseudonyms. This is not a gimmick. It is a practical choice. The situations are real. The lessons are earned.
Real data work sits inside NDAs, client confidentiality, employer policies, and internal politics. Pseudonyms let us write honestly about recurring patterns without turning the site into personal branding or corporate messaging.
Our editorial standard
We win trust by behavior, not by claims.
So we keep a simple standard:
- We define terms. If a metric matters, its definition must be explicit.
- We separate facts from assumptions. If we estimate, we label it.
- We show our work. If we make a claim, we give the method or the reasoning.
- We correct ourselves. Updates and corrections are visible.
- We prefer boring reliability over clever complexity.
The experiment
This site is an experiment in usefulness.
Can a small, pseudonymous collective build a believable, durable library of practical patterns? Can we create pages that working analysts and consultants bookmark, reuse, and share? Can we earn search traffic by solving real problems clearly?
That is the objective.
If the site becomes the place people go when they need the numbers to be right—and the delivery to be on time—then data.day worked.
Welcome.