Text analysis is a core skill for data analysts because real-world data is often messy, unstructured, and text-heavy. In this module, you’ll learn how to transform raw text into clean, usable signals using practical SQL techniques. Starting with string fundamentals like LEFT, RIGHT, LENGTH, and TRIM, you’ll extract meaningful substrings, standardize inconsistent inputs, and build structured fields such as full names and URLs.
As you progress, you’ll apply these skills to realistic business problems: identifying the longest names, cleaning product catalogs, finding the most frequently entered products, and aggregating text data across users, countries, and transactions. The module also introduces more advanced patterns like string aggregation, unnesting, and social data analysis (e.g. Twitter hashtags), helping you move from simple text manipulation to insight-driven analysis. By the end, you’ll be confident handling text data the way it appears in real analytics interviews and on the job.
Using LEFT, RIGHT and LENGTH