Excel skills that answer real questions
=SUMIFS(Amount, Region, "North", Month, "Oct")   → revenue for one region/month
=XLOOKUP(A2, Customers[ID], Customers[City])     → pull a matching value
=COUNTIFS(Status, "Returned", Month, "Oct")       → count returns
PivotTable: Rows = Region, Values = Sum of Amount  → summary in seconds

-- Which product categories earned the most in October 2026?
SELECT category,
       SUM(amount) AS revenue,
       COUNT(DISTINCT customer_id) AS customers
FROM orders
WHERE order_date >= '2026-10-01' AND order_date < '2026-11-01'
GROUP BY category
ORDER BY revenue DESC;

Project: Why did repeat purchases fall in Q3?
Question: Which customer groups stopped buying again, and why?
Data: Public e-commerce orders dataset (link)
Method: SQL cohort table → Excel/BI charts → segment comparison
Finding: Repeat rate fell most for first-time buyers from one channel
Recommendation: Test a follow-up offer for that channel's new buyers
Limits: No data on competitor pricing; one quarter only

-- Customers by first-purchase month and whether they bought again
WITH firsts AS (
  SELECT customer_id, MIN(order_date) AS first_date
  FROM orders
  GROUP BY customer_id
)
SELECT DATE_TRUNC('month', f.first_date) AS cohort_month,
       COUNT(DISTINCT f.customer_id) AS new_customers,
       COUNT(DISTINCT o.customer_id) AS returned
FROM firsts f
LEFT JOIN orders o
  ON o.customer_id = f.customer_id AND o.order_date > f.first_date
GROUP BY 1
ORDER BY 1;

-- Classic interview task: second highest salary per department
SELECT department, salary
FROM (
  SELECT department,
         salary,
         DENSE_RANK() OVER (PARTITION BY department ORDER BY salary DESC) AS rnk
  FROM employees
) ranked
WHERE rnk = 2;

Business case: "Website orders dropped 15% last week. What would you check?"
1. Clarify: all products or some? all regions? since which day?
2. Data checks: is tracking working? any missing data?
3. Internal causes: price change, site release, stock-outs, payment errors
4. External causes: holiday, competitor offer, seasonality
5. Next step: segment the drop, then recommend one test

Do I enjoy...
☐ Finding patterns in numbers?
☐ Explaining findings to non-technical people?
☐ Checking details until they are right?
☐ Asking 'why' about business results?
3-4 ticks → data analytics is worth exploring seriously.

First month: Excel — formulas, PivotTables, charts
Second month: SQL — SELECT to JOINs and GROUP BY
Third month: BI tool — Power BI or Tableau dashboards
Fourth month: Statistics basics + intro Python (pandas)
Fifth month: Three portfolio projects with write-ups
Sixth month: Interview practice, applications, networking

☐ 20 SQL problems solved (joins, aggregates, window functions)
☐ One dashboard I can walk through in 3 minutes
☐ Two-minute summary of each project
☐ Two business cases practised aloud
☐ Questions to ask the interviewer