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SQL for Data Analysis and AI

Module 09 Knowledge Check

5 questions. Pass mark 4 out of 5. Answer every question before checking the answer key below, then retry after reading the feedback.

1. LIKE '%delhi%' fails to match 'Delhi' in a case-sensitive database. The robust fix is…

2. The main risk of free-text categories like city names is…

3. A CASE expression that buckets values should always include…

4. Trimming whitespace before grouping matters because…

5. When preparing text columns as features for later analysis, you should record…

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Answer Key and Explanations

Check these only after attempting every question.

1. B - Normalise case on both sides, e.g. LOWER(column) LIKE LOWER(pattern)

Explicit normalisation makes matching behaviour independent of engine collation settings.

2. B - Spelling and spacing variants split one real category into many

'New Delhi', 'new delhi', and 'New Delhi' become three groups in a GROUP BY.

3. B - An ELSE branch so unmatched values are visible rather than silently NULL

Without ELSE, anything unexpected becomes NULL and disappears from your categories.

4. B - 'Delhi ' and 'Delhi' are different values and form separate groups

Invisible characters are a leading cause of duplicated categories.

5. B - The normalisation rules applied, so results are reproducible and reviewable

Undocumented cleaning cannot be reproduced or challenged, which breaks the evidence trail.

Practical Check

Apply this module to your own work: complete the module activity for *Text Fields, Categorisation, and Feature Preparation*, then write one sentence naming what your result shows and one naming what it does not.

Strong Answer Pattern

A strong answer names the task, the evidence used, the check performed, and the remaining limitation. It avoids "proved", "guaranteed", or "always" unless the evidence genuinely supports it.