Seven folders, no labels
An analyst opens a shared drive. There are seven sets of data. None has a clear label.
Which belong to health? Which are about shops? Which can be used for this project? Before any analysis, the data must be sorted into groups that make sense.
Key words
| Word | What it means | Example |
|---|---|---|
| Classify | To sort things into groups by a rule. | Put sales data in the retail group |
| Content | What the data actually contains. | Counts of patient visits |
| Context | The setting around the data: who made it, when, and for what use. | Made by a hotel in 2026 |
| Metadata | Data about data, such as its author, date and size. | Created 3 March by the till system |
| Sector | A group of organisations with similar work, such as health or retail. | Education |
| Dataset | A collection of related data kept together. | All till sales for March |
| CSV | A plain text file where commas split each line into columns. | bun,4,2 |
| User | The person who will work with the data and what they know. | A manager who needs a weekly count |
The cells students fill in are left blank in this preview.
By the end of this lesson
Note
I can classify a dataset by content, context and user, and place it in the right sector.
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.
Three ways to classify
| Way | It asks | Example |
|---|---|---|
| Content | What information is inside? | Counts of room bookings |
| Context | Who made it and where is it used? | A hotel, using it for planning |
| User | What does the person using it know and need? | A manager who wants a weekly count |
The cells students fill in are left blank in this preview.
Why classify at all?
The group you choose affects how the data is used and how easy later analysis is.
A dataset put in the wrong group is easy to lose. A dataset classed by its content and context is easy to find, combine and trust.
Good labels now save hours later.
Grouping by sector
Datasets are also grouped by sector: health, retail, hospitality, technological and education.
Read what the data is about and who made it. Clues in the name or the description often give the sector straight away. If a clue is missing, look at the context.
Try it: group the datasets
select sector, count(*) as datasets
from datasets
group by sector
order by sector;
-- Try it: change group by to made_by and press Run.