A lovely table that answers nothing
A bakery owner asks which days need extra staff. The analyst hands over a spotless table of daily sales, with no staff count and no opening hours.
The data is clean. It does not fit the question. Before any analysis, you must say whether the data is right for the job, and say why.
Key words
| Word | What it means | Example |
|---|---|---|
| Requirement | What the analysis must find out or show. | Busiest days for staff |
| Rationalise | To give clear reasons for a decision. | This table has the daily totals we need |
| Dataset | A collection of related data kept together. | Daily sales |
| Audience | The people who will read your findings. | The bakery owner |
| Level of detail | How much information you give: a short note or the full working. | A summary for an owner |
| Field | One named column in a table. | total |
| Gap | Something the analysis needs that the data does not hold. | No staff count |
The cells students fill in are left blank in this preview.
By the end of this lesson
Note
I can compare a dataset with what an analysis needs and explain clearly why it does or does not fit.
Starter: what you already know
Have a go
Starter: what you already know
3 questionsYour answers are marked here and are not kept. A college account keeps every student’s marks.
Worked example: needs against the table
| What the analysis needs | In the dataset? | Result |
|---|---|---|
| The day | Yes, field day | Fits |
| Total sales each day | Yes, field total | Fits |
| Number of staff | No | Gap |
| Opening hours | No | Gap |
The cells students fill in are left blank in this preview.
Four steps to rationalise
- Write the requirements of the analysis as a list.
- Compare each need with the fields in the dataset.
- Rationalise: say why it fits, or name the gaps and what to do about them.
- Present the result logically, at the level of detail the reader needs.
Try it: find the gaps
needs = ["day", "total", "staff"]
columns = ["day", "total", "rain"]
for need in needs:
if need in columns:
print(need, "fits")
else:
print(need, "is a gap")
# Try it: add "staff" to columns and press Run.
A common mistake
Warning
Many people say "the data is fine" with no reasons. A claim needs evidence. Say which needs are met, which are not, and how you know. Be clear and short.