# data · data.sql
Data Visualisation
Charts and dashboards built to make your dataset's actual finding legible.
A chart that needs the presenter to explain what it shows has already failed at its job. We choose the chart type for the data in front of us, not the default option, label everything a reader would otherwise have to ask about, and caption each figure so it stands on its own in a report.
What you get
- Chart type chosen to fit the data, not the one everyone defaults to
- Built in the tool your brief names — Python, R, Tableau or Power BI
- Labelled axes, legends and titles a marker doesn't have to guess at
- Colour choices that hold up if printed in greyscale
- One dashboard or figure set, not a slideshow of disconnected charts
- A short caption for each figure explaining what it shows
What to send first
- The dataset (or a sample of it) and where it came from
- The questions the analysis has to answer, or the model's target
- Required tools — SQL dialect, Python libraries, R, Excel version
- The report format: notebook, PDF write-up, dashboard or slides
How it runs
- 01
Send the spec
The brief, the rubric, any starter code and the versions your marker uses. A photo of the PDF is fine to begin with.
- 02
Scope and quote in writing
We read it properly, ask what is unclear, and confirm a fixed price and delivery date. A small advance confirms the order.
- 03
Build against the brief
Work is tracked task by task against the spec. Longer projects are split into milestones you can review as they land.
- 04
Tested handover
A repo that installs from a README, run against your test cases, with the write-up if your rubric asks for one.
- 05
Fixes and walkthrough
One round of fixes if a marker flags something, and a walkthrough of how it works so you can explain it.
Data Visualisation: common questions
The notebook or scripts that produced every number, so the analysis can be re-run end to end. Results pasted into a report without the code behind them are hard to defend.
No. Data is used only for your task, never shared or reused, and deleted on request once the work is signed off.
It depends on the scope of the brief, the stack and the deadline. Send the spec on WhatsApp and you get a fixed price and delivery date in writing before any work starts — no hourly meter.
Turnaround depends on scope and is agreed with the quote. Tell us the real deadline, including the timezone, and we will say honestly whether it is workable before you commit.
// related
Often paired with data visualisation
Database Design
Normalised schema design from an ER diagram through to a working database.
data.sqlSQL Query Work
Query sets solved and explained line by line, from joins to window functions.
data.sqlData Pipelines
ETL pipelines built to ingest, clean and load a dataset the way your brief specifies.
./send-brief
Send your data.
Paste the data visualisation brief into WhatsApp — the message already names the service. Scope and price come back in writing.