Overview
SQL Filtering & Search
Commands Practice
Precision SQL for real-world analytics — restricting output, identifying unique values, searching text patterns, and isolating records within ranges.
Course Learning Objectives
- Restrict query output to a specified number of rows using LIMIT and combine it with ORDER BY for Top N reporting.
- Remove duplicate values and identify unique business categories using DISTINCT.
- Search text fields using patterns with LIKE — matching values that start with, end with, or contain specific text.
- Build flexible text searches using SQL Wildcards — % for any-length sequences and _ for exactly one character.
- Filter records matching any value in a list using IN, replacing multiple OR conditions with a single clean clause.
- Isolate records within defined numeric and date ranges using BETWEEN, inclusive of both boundary values.
- Use AI tools to generate, verify, and troubleshoot filtering and search SQL queries against real business questions.
Part 1 covers LIMIT — the command that caps query output at a fixed row count. Students learn to restrict output for dataset previews, combine LIMIT with ORDER BY for ranked Top N analysis, and understand the correct SQL clause order when multiple commands are combined.
How LIMIT stops a query after a specified number of rows, regardless of table size.
Combining ORDER BY with LIMIT to retrieve top-performing records ranked by value.
Using LIMIT as the standard first query on unfamiliar tables to inspect structure.
The correct clause order: SELECT → FROM → WHERE → ORDER BY → LIMIT.
- Practice focus: retrieving focused subsets across users, transactions, products, orders, support tickets, subscriptions, and campaign events
- 8 practice queries — each with an AI prompt and a validated SQL answer
Part 2 covers DISTINCT — the command for identifying unique values in a column. Students learn to remove duplicates, explore available business categories, and retrieve unique combinations across multiple columns. DISTINCT is the first-look tool every analyst uses before building targeted filters.
How DISTINCT collapses repeated values so each unique entry appears only once.
Why DISTINCT is used on status, category, and type columns before writing filters.
Using DISTINCT to understand available product categories and business segments.
Applying DISTINCT to multiple columns to return unique row combinations.
- Practice focus: identifying unique values across users, transactions, products, orders, subscriptions, support tickets, and sessions
- 8 practice queries — each with an AI prompt and a validated SQL answer
Part 3 covers LIKE — the pattern-matching command for text searches. Students learn to find values that start with, end with, or contain specific text, and apply LIKE to names, product descriptions, campaign titles, and status fields. LIKE is the SQL equivalent of a search bar.
How LIKE matches values based on a pattern rather than an exact value.
Applying LIKE to names, categories, statuses, and business descriptions.
Using % to match text at the start, end, or anywhere inside a value.
Using LIKE when exact values are unknown — the flexible business search pattern.
- Practice focus: searching users, products, campaigns, support tickets, and subscriptions using text patterns
- 8 practice queries — each with an AI prompt and a validated SQL answer
Part 4 goes deeper into wildcard usage inside LIKE patterns. Students master both SQL wildcards — % for any-length sequences and _ for exactly one character — and learn to combine them for advanced text searches when partial information is available.
Matching zero, one, or many characters at any position in a text value.
Matching exactly one character — used for values with a known length or structure.
Building patterns that match values even when only partial information is known.
Combining % and _ in a single LIKE pattern for precise positional searches.
- Practice focus: flexible text searches across users, products, campaigns, and support tickets using % and _ patterns
- 8 practice queries — each with an AI prompt and a validated SQL answer
Part 5 covers IN — the list-based filtering command. Students learn to filter records matching any value in a specified list, replace chains of OR conditions with a single clean IN clause, and select specific business segments by category, status, or type.
How IN returns any row matching at least one value in the provided list.
IN vs OR — same results, cleaner code for filtering the same column.
Selecting records from named business categories or status groups in one clause.
Using IN to isolate meaningful business segments for analysis and reporting.
- Practice focus: filtering users, transactions, products, orders, subscriptions, support tickets, campaigns, and sessions by category and status
- 8 practice queries — each with an AI prompt and a validated SQL answer
Part 6 covers BETWEEN — the range-filtering command. Students learn to isolate records within numeric, financial, and date-based boundaries, understand that BETWEEN is always inclusive of both boundary values, and combine BETWEEN with ORDER BY for sorted, ranged business reports.
Filtering prices, amounts, and other numeric values within a defined boundary.
Isolating business activity within specific time windows using YYYY-MM-DD format.
Identifying transactions and fees within defined financial ranges for reporting.
Combining BETWEEN with ORDER BY for sorted, range-filtered analytical output.
- Practice focus: range-filtering products, transactions, orders, users, subscriptions, campaign events, and support tickets by value and date
- 8 practice queries — each with an AI prompt and a validated SQL answer
Course at a Glance
Six parts · 48 practice queries · same tables as Part 1
| Part | Command | Core Focus | Practice |
|---|---|---|---|
| Part 1 | LIMIT | Restricting output, Top N analysis, previewing datasets, combining with ORDER BY | 8 Queries |
| Part 2 | DISTINCT | Identifying unique values, removing duplicates, exploring categories | 8 Queries |
| Part 3 | LIKE | Pattern matching, text field searching, partial text filtering, business search logic | 8 Queries |
| Part 4 | Wildcards | % (any characters), _ (one character), flexible and advanced pattern matching | 8 Queries |
| Part 5 | IN | Filtering multiple values, replacing OR conditions, list-based business category selection | 8 Queries |
| Part 6 | BETWEEN | Numeric ranges, date windows, financial thresholds, inclusive range-based filtering | 8 Queries |
Every practice question in this course includes a business question, an AI prompt for ChatGPT or Copilot, the validated SQL answer, and guidance on interpreting the result. Students learn to prompt effectively, verify SQL correctness, troubleshoot filtering logic, and connect query output to real business decisions.
What You Leave With
Six filtering and search commands. Forty-eight practice queries. A complete SQL search toolkit.
The ability to cap query output for dataset previews and Top N business reports.
Instant identification of unique business values, categories, and segment combinations.
Flexible text search across any column — start with, end with, or contains patterns.
Advanced pattern building using % for any-length and _ for single-character positions.
Clean list-based filtering for multi-value business category and status selection.
Inclusive range filtering for numeric, financial, and date-based business boundaries.
The ability to prompt, verify, and troubleshoot AI-generated filtering SQL in a professional workflow.
Certificate of Completion from the Canadian Institute of Artificial Intelligence (CiAI), powered by DataSoSi.
