Comprehensive SQL roadmap posted

A detailed SQL study roadmap from Shraddha Bharuka is circulating on X, laying out a step-by-step path from basic queries to analytics and ETL work. (x.com) The post breaks SQL into the core command families learners usually meet first: Data Definition Language for creating and changing tables, Data Manipulation Language for inserting and updating rows, and Data Query Language for reading data with `SELECT`. (geeksforgeeks.org) It then moves into joins and subqueries, which are the techniques that let one query pull related data from multiple tables or nest one query inside another. PostgreSQL’s tutorial describes joins as combining rows from two tables with a matching condition, while Microsoft’s SQL Server docs define a subquery as a query nested inside another statement. (postgresql.org) (learn.microsoft.com) The roadmap’s later sections focus on window functions, the part of SQL analysts use for rankings, running totals, moving averages, and period-over-period comparisons without collapsing rows. PostgreSQL and BigQuery both describe window functions as calculations performed across a related set of rows while still returning a value for each row. (postgresql.org) (cloud.google.com) That sequence mirrors how SQL is used on the job. Data teams usually start with selecting and filtering records, then add joins, grouping, and common table expressions before moving into window functions for dashboards, campaign reporting, and retention analysis. (learn.microsoft.com) (postgresql.org) The thread also includes interview-heavy functions and performance advice, which pushes it beyond syntax memorization. BigQuery’s performance guide, for example, recommends avoiding `SELECT *`, reducing the amount of data scanned, and being careful with `ORDER BY` placement because those choices can sharply affect query cost and speed. (cloud.google.com) On Microsoft SQL Server, performance guidance around joins also turns into execution details: the database engine can choose nested loops, merge joins, hash joins, or adaptive joins depending on table size, indexes, and data distribution. That is the point where “writing SQL” turns into understanding how the database actually runs it. (learn.microsoft.com) The post lands into a crowded market of SQL guides, but its appeal is the packaging: one thread that starts with table creation and ends with analytics patterns and ETL-adjacent tasks. Roadmap.sh, GeeksforGeeks, and other tutorial sites publish similar staged plans, which suggests sustained demand for condensed learning maps rather than isolated lessons. (roadmap.sh) (geeksforgeeks.org) For people trying to break into analyst or data roles, the practical order in Bharuka’s thread is the point: learn how to read tables, combine them, summarize them, and then calculate trends row by row. That is still the backbone of most dashboard and reporting work, no matter which database sits underneath. (x.com) (cloud.google.com)