SQL Fundamentals for Analysts (DA-101)
The head of growth drops a message in your channel: "Which region drove the most revenue last quarter, and who are our biggest customers there?" The answer is sitting in a database right now. Nobody is going to hand it to you in a tidy chart — you have to ask the data yourself, in a language it understands. That language is SQL, and this course teaches you to speak it well enough that a stakeholder acts on your answer without second-guessing it.
DA-101 is the anchor course of the School of Data Analytics & Business Intelligence. It is written for people who have never queried a database and do not want a computer-science detour to get started. Every lesson begins with a real person asking a real question, and ends with you writing the query that answers it. You will not memorize syntax for its own sake; you will learn the handful of clauses that answer the vast majority of analytical questions, and learn to reason about whether your answer is actually correct.
- Read a single table with intent using
SELECT,WHERE, andORDER BY - Summarize data into decision-ready numbers with
GROUP BY, aggregate functions, andHAVING - Combine customer and order data with
INNER JOINandLEFT JOIN, and spot the fan-out bug that silently inflates totals - Translate a stakeholder's plain-English question into a query and its result back into a one-line answer they can act on
Who this course is for
This is the on-ramp to the whole school. It assumes no programming background — if you can read a sentence and a small table, you can do this course.
- The fresh graduate building a first analyst portfolio, who needs to turn "I know Excel a bit" into "I can pull the number myself."
- The spreadsheet power user in ops, finance, or marketing who has hit the ceiling of pivot tables and wants the tool analysts actually use.
- The career switcher who keeps seeing "SQL required" on every analyst job posting and wants to make that line true.
Prerequisites
None. DA-101 is the hard gate for everything at the 200 level and above, so it
assumes nothing before it. You do not need a database installed, a paid tool,
or a cloud account. Lesson practice runs in the SQL Kingdom playground in your
browser, and the end-of-course lab runs on your own machine using Python's
built-in sqlite3 — zero installation.
Modules
DA-101 is roughly fourteen hours across seven modules. This first slice delivers three core lessons and a capstone lab that ties them together against a single stakeholder question.
| # | Module | What you leave with |
|---|---|---|
| 1 | Relational thinking | Tables, rows, and keys, and why analysts care |
| 2 | Select, filter, sort | Reading one table to answer a pointed question |
| 3 | Aggregation and GROUP BY | Turning rows into decision-ready summaries |
| 4 | Joins for analysts | Combining tables without inflating your totals |
| 5 | Subqueries and CTEs | Composing questions from smaller questions |
| 6 | Window functions for analysts | Running totals, rankings, period-over-period |
| 7 | Query hygiene | Readable SQL a teammate can trust and reuse |
The three lessons and the lab below cover the heart of Modules 2, 3, and 4 — the clauses that answer most day-to-day analytical questions.
Outcomes
By the end of DA-101 you can:
- Take a vague stakeholder request and pin it down to a specific, answerable query.
- Filter and sort a table to surface exactly the rows a decision needs.
- Aggregate raw rows into the totals, counts, and averages a report is built on.
- Join tables correctly and defend your numbers against the most common way join queries go wrong.
Where this leads
DA-101 is the prerequisite the rest of the school stands on. The aggregation and join skills here feed directly into DA-102 (translating spreadsheet workflows to SQL), the Python analysis in DA-201, and every dashboard you build in DA-202. The school converges on DA-350, an end-to-end BI capstone where you model, analyze, and present a multi-source dataset — and it opens with the exact skill this course closes on: answering a stakeholder's question in SQL.
Do the lessons in order. Each one builds on the last: sorting a table (Lesson
- becomes summarizing it (Lesson 2) becomes joining it to another table (Lesson 3), and the lab pulls all three together into one real analysis.