Excel, SAP, Oracle & automation tips — plus wacky facts
Query data like a pro — explained for Excel users.
Query data like a pro — explained for Excel users.
📄 27 articles⬇️ 27 with practice files🕒 Updated 28 Sep 2026
🎓 Start here: Rust Course → 🎓 Start here: Java Course → 🎓 Start here: R Course →Final project: recency, frequency and monetary scores with NTILE, customer segments, outstanding receivables per customer and average collection days by payment mode.
Read article →Read EXPLAIN QUERY PLAN, see SCAN turn into SEARCH with an index, build covering indexes, and learn why functions on columns stop indexes working.
Read article →Turn rows into columns with conditional aggregation: sales by status per region, orders per quarter, payment-mode mix and actual vs target with % achieved.
Read article →Walk a manager hierarchy, build reporting paths, total a team's salary cost and generate a calendar to find days with no orders, using WITH…
Read article →Combine and compare result sets: one list from two tables, customers who bought both products, customers who never bought one, and activity timelines with…
Read article →Find unpaid orders with LEFT JOIN ... IS NULL and NOT EXISTS, list employees with their managers via a self-join, and fill zero months…
Read article →Compare each row with the previous or next one: month-on-month growth %, days between a customer's orders and the next order date with LAG…
Read article →Running totals, year-to-date by region, 3-month moving averages and share of total with SUM() OVER and window frames (ROWS BETWEEN).
Read article →Rank customers, find the top customer in each region and each customer's latest order with ROW_NUMBER, RANK, DENSE_RANK and PARTITION BY.
Read article →Write readable SQL with CTEs: name a subquery once, chain several steps, compare each customer with the average and compute category shares.
Read article →Put the course together: build a half-year sales report from shop.db with total sales, GST, top customer, best month, cancellation rate and a region…
Read article →Save a query as a view: build an order_lines view joining orders, customers and products, query it like a table, use views for reports…
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