PixelUp Agency L4 — Keep It Clean
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Slide 01 / 06
Spot the Problems
A new team member added brand deal data. Can you see what went wrong?
PixelUp — L4
CreatorBrandDeal Value (£)StatusPlatform
@ZaraPlaysRazer2500ActiveYouTube
@ZaraPlaysG-Fuel1800CompletedYoutube ❌
@CoastlineEatsHelloFresh900pending ❌TikTok
@CoastlineEatsNinja Kitchenware-150 ❌ActiveTikTok
@TechWithTeoSquarespace2200CANCELLED ❌YouTube
@StudioKaiAdobe1200Activeinstagram ❌
@RushRunnersGarmin1500On Hold ❌YouTube
5 problems in one dataset. Each one would break our COUNTIF and IF formulas — because "Youtube" ≠ "YouTube" and "pending" ≠ "Pending". The data looks fine to a human but the computer treats them as completely different values.
Teacher Notes
Ask students: "How many errors can you see?" before revealing the highlighted cells. This mimics a real audit task. Key insight: computers are case-sensitive and literal — "YouTube" and "Youtube" are different strings. Even a trailing space causes a mismatch. This is exactly why NHS databases, airline booking systems, and bank records use validation rules. Real cost: the NHS estimates data quality issues cost around £10 billion annually.
Slide 02 / 06
Types of Validation
Five ways to protect your data at the point of entry
PixelUp — L4
📋
List Check
Only allows values from a pre-approved list. Example: Status must be "Active", "Pending", "Completed", or "Cancelled" — nothing else accepted.
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Range Check
Ensures a number falls within acceptable limits. Example: Deal Value must be greater than £0 — negative values are impossible.
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Type Check
Ensures data is the correct data type. Example: Deal Length must be a whole number (integer) — "thirty" or "30.5" would be rejected.
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Length Check
Ensures text is a certain number of characters. Example: A UK phone number must be exactly 11 digits — not 10, not 12.
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Presence Check
Ensures a value has been entered — the field can't be left blank. Often shown by an asterisk (*) on web forms.
Important: Validation limits reasonable values, not correct values. A deal value of £9,999 might pass range validation but still be wrong if the actual deal was £999. Validation reduces mistakes — it doesn't eliminate them.
Teacher Notes
Ask students to give a real-world example of each type before moving on. List check: exam grade dropdowns on school systems. Range check: age must be 0–120 on a medical form. Type check: national insurance number must be letters+numbers. Length check: sort code must be 6 digits. Presence check: email address can't be left blank on a checkout form. This recall exercise reinforces the concepts before the practical work.
Slide 03 / 06
Data Validation in Google Sheets
Adding rules that prevent bad data entering your spreadsheet
PixelUp — L4
Adding a Dropdown List Validation
  • 1Select the cells you want to validate (e.g., the entire Status column, D2:D11)
  • 2Go to Data → Data validation
  • 3Click + Add rule
  • 4In the "Criteria" dropdown, choose "Dropdown"
  • 5Type your allowed values: Active, Pending, Completed, Cancelled (one per field)
  • 6Under "If the data is invalid", choose "Reject the input"
  • 7Click Done
Adding a Number Range Validation
  • 1Select the Deal Value column (C2:C11)
  • 2Go to Data → Data validation → Add rule
  • 3In Criteria, choose "Greater than"
  • 4Enter 0 in the value field
  • 5Choose "Reject the input"
  • 6Add a helpful error message: "Deal value must be greater than £0"
After adding rules, try entering an invalid value — Google Sheets shows a red warning and rejects it. This is exactly the protection PixelUp needs.
Teacher Notes
Live demo this in Google Sheets on the projector. Show: (1) entering "pending" lowercase — rejected. (2) Entering "Active" from the dropdown — accepted. (3) Entering -100 in Deal Value — rejected with the error message you configured. This demo is critical — seeing it rejected in real time makes the concept concrete. The "Reject the input" option is key — without it, Sheets only warns, doesn't prevent.
Slide 04 / 06
Conditional Formatting
Let colour tell the story — instantly
PixelUp — L4
What is conditional formatting?
Rules that automatically change the colour, font, or style of a cell based on its value. No formula needed — the formatting updates as the data changes.
Add a rule in Google Sheets
  • 1Select the Status column
  • 2Go to Format → Conditional formatting
  • 3In "Format rules", choose "Text is exactly"
  • 4Enter Active
  • 5Choose a green fill colour
  • 6Click Add another rule and repeat for Pending (amber) and Cancelled (red)
What it looks like
✅ Active — Green background
⏳ Pending — Amber background
❌ Cancelled — Red background
⭐ £5,000+ Deal — Purple bold
At a glance, PixelUp can see which deals need attention without reading every cell.
Teacher Notes
Multiple conditional formatting rules can apply to the same cell — the order matters (top rule wins when conditions conflict). The high-value deal rule uses "Greater than" with a number, not "Text is exactly". For the purple bold rule, students select the Deal Value column, add a "Greater than 5000" rule, and set the formatting to bold with a violet background — show this sequence clearly. The visual payoff is immediate and satisfying for students.
Slide 05 / 06
Validation in the Real World
Every system you interact with uses these exact techniques
PixelUp — L4
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Online check-in
Passport number: length check (9 chars), type check (letters + numbers), presence check (can't board without it). Date of birth: range check (must be a valid past date).
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NHS patient records
NHS number: exactly 10 digits (length check). Blood type: dropdown list (A+, A-, B+, B-, AB+, AB-, O+, O-). Allergies: presence check with default "None known".
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E-commerce checkout
Card expiry: format check (MM/YY), range check (must be future date). Postcode: format check (UK postcode pattern). Quantity: range check (1–99, can't order 0 or -5 items).
Validation doesn't guarantee accuracy. If someone types the wrong postcode but it's still a valid postcode format, validation passes it. You can only validate the structure of data — not whether the content is true or correct. This is why presence checks and other checks are combined in real systems.
Teacher Notes
Ask: "Has anyone ever seen a form reject their input with a red message? What was the validation rule?" Collect 2–3 examples. The limitation point (validation ≠ correctness) is important for exam purposes in higher year groups — a student could enter their brother's date of birth and it would pass all validation. This is also a good cybersecurity hook: social engineering attacks exploit the gap between "valid format" and "actually correct".
Slide 06 / 06
Validation Doesn't Guarantee Accuracy
And today's tasks
PixelUp — L4
The gap validation can't fill
Our Status dropdown allows: Active, Pending, Completed, Cancelled. What if the correct status is "On Hold" for a delayed deal? Our validation would reject it — even though it's the right answer.
This is why validation rules need to be designed carefully in consultation with users — not just imposed. What values do people actually need to enter?
✅ Today's Tasks
  1. Import starter.csv — spot the 5 deliberate errors
  2. Add dropdown validation to the Status column
  3. Add dropdown validation to the Platform column
  4. Add number validation: Deal Value must be > £0
  5. Add conditional formatting: Active/Pending/Cancelled colours
  6. Add conditional formatting: highlight deals > £5,000
  7. Fix the bad data rows using the validated dropdowns
Teacher Notes
Students often ask: "Why not just fix the errors manually?" — the answer is scale. PixelUp has 10 deals today. In a real agency with 500 creators and 2,000 brand deals per year, manual checking is impossible. Automated validation catches errors at the moment of entry, before they propagate through linked spreadsheets and reports. Ask students to predict before checking: "How many of the 10 rows have errors?" — the answer from the CSV is 5.