Lead-Lag Navigation

To improve customer satisfaction and inventory planning, let us say we want to analyze how each customer's purchase amount has changed over time.

Did their spending increase from one order to the next? Did it drop? For this, we need to compare values across different rows, specifically, a current row with its previous or next row in a sequence. This is where the lead-lag navigation pattern becomes essential.

In this lesson, we’ll learn how to compare rows using the LEAD() and LAG() window functions. By the end, we’ll be able to calculate changes, detect trends, and navigate ordered data effectively.

We’ll learn how to:

• Understand the use of LEAD() and LAG() in SQL.

• Apply this pattern to analyze changes between consecutive records.

• Use it to compare rows across time, transactions, or any ordered dimension.

• Build insight-driving queries using the OnlineStore database.

Pattern overview

Category:

• Sequencing & Hierarchical Patterns

Intent:

To access data from the previous or next row within a defined sequence.

Motivation:

Many analytical questions require comparing current values to prior or future ones, such as tracking changes in prices, purchase behavior, or shipping performance. Without LEAD() or LAG(), these comparisons often require complex self-joins, which are harder to read and maintain.

Also known as:

• Row-to-row comparison

• Temporal shift

• Row navigation

Structure