Sep 13, 2025 · 2 min read · The goal of this project was to analyze employee turnover trends and uncover the key drivers behind attrition. By using a data-driven approach, HR can design better retention strategies and improve workforce stability. Key questions addressed: Which...
Join discussionSep 4, 2025 · 3 min read · Introduction Cumulative totals, running sums, and ranking are some of the most common analytics requirements. Whether you are analyzing sales over time, customer growth, or employee salaries, you will often need to calculate metrics that keep growing...
Join discussionAug 25, 2025 · 4 min read · SQL Server window functions are essential for analytics, reporting, and business intelligence. They allow you to perform calculations across sets of rows while retaining row-level detail. In this article, we’ll explore the most important window funct...
Join discussionJul 14, 2025 · 2 min read · 1. OVER() Applies a function over all rows if not partitioned. SELECT name, salary, AVG(salary) OVER() AS avg_salary FROM employees; Calculates the overall average salary for every row. 2. PARTITION BY Divides result into groups (like GRO...
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Jun 17, 2024 · 5 min read · Hey there, fellow data engineers! This week's blog aims to delve into the various methods of accessing columns in PySpark, explore the different types of aggregate functions, and understand the utility of window functions. By the end of this post, yo...
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Mar 14, 2024 · 6 min read · Understanding Window Functions in SQL Server In the realm of database operations, while regular aggregate functions dominate by working on entire tables through the GROUP BY clause, a less-explored yet highly potent tool exists—the window functions. ...
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