Description

Build practical SQL analysis skills through a complete, reproducible workflow using a realistic synthetic service-delivery database.

You will inspect tables, columns, keys, and relationships before writing focused queries. You will then filter and derive fields, summarize performance, join related tables, organize complex logic with common table expressions, rank results with window functions, and detect data-quality problems.

The practical emphasizes trustworthy analysis. You will check query grain, join cardinality, row counts, missing values, unmatched keys, and reconciliation totals before interpreting results.

By the end, you will have produced reusable SQL queries, exported analysis tables, a summary figure, and a documented set of findings.

What You Will Practise

relational database and schema inspection;
SELECT, WHERE, CASE, ORDER BY, and calculated fields;
grouped summaries with COUNT, SUM, AVG, and conditional aggregation;
INNER JOIN and LEFT JOIN with cardinality checks;
common table expressions and subqueries;
window functions for ranking and within-group comparison;
missing-value, duplicate, range, and unmatched-key checks;
query validation and total reconciliation;
reproducible export to CSV and PNG; and
careful separation of results, interpretation, and action.

Included

browser-based online practical;
synthetic SQLite database generator;
complete Python-driven SQL workflow;
reusable SQL queries embedded in the workflow;
generated example tables, figure, and quality-control manifest; and
learner README and environment instructions.

Please note: The dataset is synthetic and intended only for teaching and workflow testing. This is a digital product. No physical item will be shipped.