How can you filter data with SQL using multiple conditions?

You can combine AND and OR conditions. Use parentheses to control the order of evaluation, just like in mathematics. Common mistakes: 1. SQL evaluates conditions from left to right, but AND takes precedence over OR. Misunderstanding this can lead to unexpected results. 2. When filtering, remember that comparisons with NULL using standard operators (=, !=, <, >) result in NULL, not true or false. Use IS NULL or IS NOT NULL. 3. Be aware of the percent sign (%) and underscore (_) in the LIKE clause. % matches any sequence of characters, and _ matches any single character. 4. Performance-related: Ensure that the columns used in the WHERE clause are indexed appropriately, especially in large tables.

Drawing from my expertise, I'd like to share that the art of filtering data with SQL using multiple conditions is a cornerstone of effective database management. The combination of AND, OR, and NOT operators allows for a nuanced approach to data retrieval. For instance, the AND operator is pivotal when you need to narrow down results to meet all specified criteria simultaneously. Conversely, the OR operator is your go-to when any of the conditions suffice, offering flexibility in the results. The NOT operator, often used with other conditions, is essential for excluding specific data points. Mastering these operators enables you to construct complex queries and extract precisely the data you need.

Having indexes in tables - will improve the query performance with filters allowing the database engine to locate relevant rows more quickly. For complex queries, it is better to filter data at each stage to reduce the run time. Also to understand the performance implications of the queries, for large datasets, use tools like "EXPLAIN" to analyze query execution plans.

Filtering data effectively also means being mindful of data quality and integrity. Understand the implications of the conditions used and how they might affect the results in unexpected ways. For example, consider how NULL values are handled in your conditions and the impact of different isolation levels on the data retrieved.

Considering my in-depth knowledge of this industry, I'd say that efficient SQL querying is an art. Use aliases for brevity and clarity, and comments to guide readers through your logic. Formatting with indentation and line breaks is crucial for readability. Always test queries on a sample dataset to iron out any issues before execution. Finally, the DISTINCT keyword is invaluable for eliminating duplicates, ensuring clean and precise results. These tips don’t just make your SQL queries functional; they make them robust and user-friendly.

I find the use of DISTINCT to come in very handy, especially in a subquery that is selecting a foreign key from a detail table. The use of HAVING can also be invaluable in selecting summarized data in one pass.