DATA ANALYST FOUNDATIONS — MODULE 05
Dashboards & clear explanations. Edition 2026-10-15.5.

START
1. Read dashboard_brief.txt and metric_dictionary.txt.
2. Keep orders_verified.csv unchanged. It is an exact copy of Module 4's verified
   April–May 2026 Northstar Shop data: 44 orders, 40 completed, all fictional.
3. Open dashboard_starter.html locally as a layout scaffold. It has prompts only,
   no calculated metrics and no working filters. Recreate it in a local spreadsheet
   or dashboard tool, or edit its HTML if you choose. No coding is required.
4. Attempt each task in learner_worksheet.txt. Keep editable calculations linked
   to your source and record filter/denominator rules.
5. Open dashboard_solution.html in your browser after attempting the exercises.
   It works offline with embedded data, no libraries, installs or network calls.
   Initial view May/All; controls recalculate the embedded fixture only. They do
   not read a neighbouring CSV, save preferences or refresh from a live source.
6. Compare with expected_states.json and worked_solutions.txt. Use
   review_checklist.txt to record actual observations and unresolved issues.

FILES
orders_verified.csv: unchanged source. UTF-8, comma delimiter, decimal point.
Dates ISO YYYY-MM-DD; import IDs as text. Blank delivery is missing, not zero.
dashboard_starter.html: editable learner layout scaffold.
dashboard_solution.html: complete offline interactive worked example.
wireframe.svg: downloadable reading-order diagram with a text description.
dashboard_brief.txt: audience, decision, measures, filters and scope.
metric_dictionary.txt: field/measure definitions and unavailable cases.
learner_worksheet.txt: seven exercises and final rubric.
worked_solutions.txt: calculations, explanations and presentation outline.
review_checklist.txt: expected/observed evidence prompts and handover checklist.
expected_states.json: independently specified view results and tolerances.
README.txt: this guide.

METHOD
Completed value is not audited revenue or profit. AOV is value/count. May has an
April baseline for the same channel; March and prior two-month source absent.
A zero prior baseline makes percentage change unavailable. Empty selected groups
have zero additive totals/counts but unavailable averages/coverage.
Delivery means use measured completed orders only, with measured/eligible counts.
April store n=2 includes verified A020 at EUR 1,000. Do not silently exclude it.
Bar lengths start at zero and rescale to values displayed in that view. Do not
compare pixel lengths across screenshots with different filters/scales.
The empty control option is a synthetic test selection, not a real channel.
Material edition is not a live-ingestion timestamp. Changes to the CSV require
rebuilding your report; the supplied worked HTML embeds a fixed source copy.
The dashboard is a learning example; no upload, login, registration or payment.
There is no automatic assessment. Label portfolio use as fictional guided work.

METHOD REFERENCES
W3C chart alternatives: https://www.w3.org/WAI/tutorials/images/complex/
Colour: https://www.w3.org/WAI/WCAG22/Understanding/use-of-color.html
Keyboard: https://www.w3.org/WAI/WCAG22/Understanding/keyboard.html
References explain selected usability concerns, not certification of the example.
Corrections: support@datacareerhub.io; include module/version and reproducible case.