Advanced Window Function Patterns
As you move deeper into business intelligence analytics, advanced window function patterns like LAG(), LEAD(), and PERCENT_RANK() allow you to uncover trends, compare periods, and evaluate performance in new ways. These functions help you go beyond simple aggregations and rankings, offering richer insights into your business data.
123456789SELECT d.date, s.amount AS sales, LAG(s.amount) OVER (ORDER BY d.date) AS previous_sales FROM sales s JOIN dates d ON s.sale_date_id = d.date_id ORDER BY d.date;
By using the LAG() function, you can compare each day's sales to the previous day's sales. This lets you analyze trends such as whether sales are increasing, decreasing, or remaining steady over time. For example, you might quickly spot a drop in sales on a particular date, prompting further investigation into possible causes.
The LAG() and LEAD() window functions let you access data from previous or following rows within the result set. LAG() retrieves a value from a preceding row, while LEAD() retrieves from a following row. These are powerful tools for trend analysis, such as comparing current and previous values or forecasting.
123456SELECT ep.employee_id, ep.sales_achieved AS sales, PERCENT_RANK() OVER (ORDER BY ep.sales_achieved) AS percentile FROM employee_performance ep;
Using PERCENT_RANK() helps you evaluate employee performance by showing each employee's relative standing among their peers. A percentile rank close to 1 means the employee is among the top performers, while a value near 0 indicates a lower rank. This can be useful for identifying high achievers or employees who may need additional support.
You can combine multiple window functions in a single query to build comprehensive business reports. For instance, using both LAG() and PERCENT_RANK() together allows you to see not only how an employee's performance compares to others, but also how it has changed over time. This approach provides a more complete view of trends and rankings, supporting better decision-making.
1. What does the LAG() function do in SQL?
2. How can percentiles help in employee performance analysis?
3. Give an example of using LEAD() in a business scenario.
Thanks for your feedback!
Ask AI
Ask AI
Ask anything or try one of the suggested questions to begin our chat
Can you explain how the LEAD() function works and when to use it?
How can I combine LAG() and PERCENT_RANK() in a single query?
Can you give more examples of advanced window function patterns?
Awesome!
Completion rate improved to 5.56Advanced Window Function Patterns
Swipe to show menu
As you move deeper into business intelligence analytics, advanced window function patterns like LAG(), LEAD(), and PERCENT_RANK() allow you to uncover trends, compare periods, and evaluate performance in new ways. These functions help you go beyond simple aggregations and rankings, offering richer insights into your business data.
123456789SELECT d.date, s.amount AS sales, LAG(s.amount) OVER (ORDER BY d.date) AS previous_sales FROM sales s JOIN dates d ON s.sale_date_id = d.date_id ORDER BY d.date;
By using the LAG() function, you can compare each day's sales to the previous day's sales. This lets you analyze trends such as whether sales are increasing, decreasing, or remaining steady over time. For example, you might quickly spot a drop in sales on a particular date, prompting further investigation into possible causes.
The LAG() and LEAD() window functions let you access data from previous or following rows within the result set. LAG() retrieves a value from a preceding row, while LEAD() retrieves from a following row. These are powerful tools for trend analysis, such as comparing current and previous values or forecasting.
123456SELECT ep.employee_id, ep.sales_achieved AS sales, PERCENT_RANK() OVER (ORDER BY ep.sales_achieved) AS percentile FROM employee_performance ep;
Using PERCENT_RANK() helps you evaluate employee performance by showing each employee's relative standing among their peers. A percentile rank close to 1 means the employee is among the top performers, while a value near 0 indicates a lower rank. This can be useful for identifying high achievers or employees who may need additional support.
You can combine multiple window functions in a single query to build comprehensive business reports. For instance, using both LAG() and PERCENT_RANK() together allows you to see not only how an employee's performance compares to others, but also how it has changed over time. This approach provides a more complete view of trends and rankings, supporting better decision-making.
1. What does the LAG() function do in SQL?
2. How can percentiles help in employee performance analysis?
3. Give an example of using LEAD() in a business scenario.
Thanks for your feedback!
