Combine data from multiple tables using various types of JOINs while filtering or manipulating data with subqueries for detailed analysis.
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Apply functions over a set of rows relative to the current row to perform complex calculations like ranking or running totals.
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Define temporary result sets using the WITH clause for clearer, more reusable SQL queries, including handling hierarchical data with recursion.
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Transform rows into columns to summarize data, making it easier to read & analyze distinct values from one column across multiple columns.
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Create adaptable SQL queries that dynamically change based on variable conditions or inputs, enhancing query flexibility and reusability.
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Utilize functions like COUNT(), SUM(), AVG() with GROUP BY and HAVING for detailed data aggregation and analysis.
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Search for specific patterns within data using LIKE, SIMILAR TO, or regular expressions, essential for data cleaning and text analysis.
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Analyze time-series data by aggregating, comparing, and manipulating dates & times, essential for trend analysis and forecasting.
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