SQL & Spreadsheets for Analysts

What you will be able to do

• You will be able to build spreadsheet formulas with absolute and relative references and the core functions analysts rely on, including IF, COUNTIF, and XLOOKUP.
• You will be able to summarize and slice a dataset with pivot tables to answer questions without writing a formula.
• You will be able to write SQL SELECT queries that filter rows with WHERE and sort and limit the results.
• You will be able to write precise filters using comparison and logical operators, IN, BETWEEN, LIKE, and correct NULL handling.
• You will be able to combine data from multiple tables using INNER JOIN and LEFT JOIN on matching keys.
• You will be able to aggregate data with GROUP BY, COUNT, SUM, and AVG, and filter grouped results with HAVING.
• You will be able to find and fix common data quality problems: duplicates, inconsistent formatting, wrong data types, and missing values.
• You will be able to turn a messy raw file into a clean, validated, documented dataset that is ready to analyze.

What is inside

4 modules, 8 lessons. Each module ends in a graded quiz and most carry an assignment.

1. 01

   Spreadsheets: The Analyst's Workbench

   Every analyst starts in a spreadsheet, and this module makes it your fastest tool. You will move from typing answers by hand to writing formulas, mastering relative and absolute cell references, and putting the daily-driver functions IF, COUNTIF, and XLOOKUP to work. Then you will build pivot tables that summarize and slice thousands of rows in seconds, so you can answer real questions from a workbook without touching a single row by hand.

   2 lessons · 5 quiz questions

2. 02

   Querying Data with SQL

   When data lives in a database, SQL is how you get it out, and it all begins with the SELECT statement. This module teaches you to choose columns, filter rows with WHERE, and sort and cap your results, then to write precise filters with comparison and logical operators, IN, BETWEEN, and LIKE. You will also learn the careful handling that NULL demands, so your filters return exactly the rows you intend and no others.

   2 lessons · 5 quiz questions · assignment

3. 03

   Joining and Aggregating in SQL

   Real analysis almost never fits inside a single table or a single row. Your customer list sits in one table, the orders those customers placed sit in another, and the answer a manager actually wants (who spent the most, how many orders shipped, what the average basket was) lives in the space between them. This module teaches the two moves that get you there. First you combine tables with INNER JOIN and LEFT JOIN, matching them on the keys they share, and you learn the quiet difference between the two that decides whether a customer with no orders vanishes from your report or shows up with a blank. Then you roll many rows up into totals and averages with GROUP BY and the aggregate functions COUNT, SUM, and AVG, and you filter those groups with HAVING to answer questions like which customers spent more than 1000 last quarter. Everything is taught on one small orders database you could rebuild by hand, so the mechanics stay concrete instead of abstract.

   2 lessons · 5 quiz questions

4. 04

   Cleaning and Preparing Messy Data

   Real data arrives messy, and analysts spend more time cleaning it than analyzing it. In this closing module you hunt down duplicates, inconsistent text and dates, wrong data types, and missing values, and fix them in both spreadsheets and SQL. You finish by turning a raw file into a standardized, validated, and documented dataset that is ready for analysis and safe to share.

   2 lessons · 5 quiz questions · assignment