Milestone 1 — first clean report
Dataset: a sales sheet with 1,000+ rows
☐ Remove duplicate orders
☐ Fix dates stored as text
☐ TRIM extra spaces in names
☐ Add a month column: =TEXT(B2,"mmm-yy")
☐ Pivot: revenue by month and region
☐ One chart + three written observations

Vague question → measurable question
'Are sales doing well?'
→ 'Is monthly revenue this quarter higher than the same months last year?'
'Are customers happy?'
→ 'What share of orders were returned or got a low rating last month?'
Practise rewriting 5 vague questions every week.

-- Milestone 2a: top 5 customers by revenue in the last quarter
SELECT c.customer_name,
       SUM(o.amount) AS revenue
FROM orders o
JOIN customers c ON c.customer_id = o.customer_id
WHERE o.order_date >= '2026-07-01' AND o.order_date < '2026-10-01'
GROUP BY c.customer_name
ORDER BY revenue DESC
LIMIT 5;

import pandas as pd

df = pd.read_csv("orders.csv", parse_dates=["order_date"])
df = df.drop_duplicates("order_id")
monthly = (df.set_index("order_date")
             .resample("MS")["amount"].sum())
print(monthly.tail(6))
print("Median order value:", df["amount"].median())

Portfolio checklist
☐ Excel dashboard with Power Query cleaning
☐ SQL case study with written findings
☐ Power BI report with a data model
☐ Python notebook on a messy dataset
☐ One-paragraph summary for each
☐ All links open without login
☐ Resume links to the portfolio

Project story in 60 seconds (STAR)
Situation: A retail dataset showed falling revenue in two regions.
Task:      Find the cause and suggest actions.
Action:    Cleaned 3 tables, joined them in SQL, compared price,
           volume and product mix, built a Power BI page.
Result:    Found the drop came mainly from one category's volume;
           recommended a stock and promotion review.
Practise aloud until it fits in a minute.

Weekly Learning Log
Week: ____  Stage: 1 / 2 / 3
Hours practised: ____
New skill: ______________
Something I struggled with: ______________
How I solved it (or plan to): ______________
Milestone progress: ____%
Next week's focus: ______________

Milestone Tracker
Stage 1
  ☐ First clean Excel report
  ☐ Pivot dashboard with 3 observations
Stage 2
  ☐ 30 SQL practice queries
  ☐ Power BI two-page dashboard
  ☐ pandas cleaning notebook
Stage 3
  ☐ Two business case studies
  ☐ Portfolio page live
  ☐ Three mock interviews

Confidence Check (1-5)
Excel formulas and pivots    ___
SQL joins and grouping       ___
Power BI modelling           ___
pandas cleaning              ___
Explaining findings          ___
Answering interview questions ___
Lowest score = next week's focus