Advanced Analytics with Window Functions in PostgreSQL

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Introduction: Elevating Analytics with Advanced Window Functions

In the realm of data analytics, window functions in PostgreSQL are akin to a Swiss Army knife, offering a versatile set of tools to glean deeper insights from your data. While basic window functions provide a solid foundation, advanced analytics demands more. In this comprehensive guide, we’ll delve into the world of advanced window functions and unveil their potential to supercharge your data analysis.

Section 1: Moving Averages — Smoothing Trends

Moving averages are invaluable for smoothing out noisy data, making trends more apparent. The `AVG()` window function, combined with the `ROWS BETWEEN` clause, allows you to calculate moving averages over a specified window.

This query computes a six-day moving average, helping to identify trends amid fluctuations.

Section 2: Percentile Calculations…