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SQL for Data Analysis

Learn SQL the way working analysts use it: query, join, summarise and analyse real business data, then prove your skills with two portfolio projects.

ECreated byEduBenchers English 52 Lessons 13:42:37 Hours Certificate
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About course

Almost every data job starts with the same skill: getting the right answer out of a database. Managers ask questions like "which city drove last month's revenue?" or "are new customers coming back?", and the answer is sitting in tables with thousands or millions of rows. SQL is how analysts find it. This course takes you from your very first SELECT to the analysis that companies actually run: business metrics, retention cohorts, funnels, data cleaning and reports.

What you'll learn

  • Databases and setup: tables, keys, PostgreSQL and pgAdmin, loading a real practice database, and how SQL runs your query
  • Querying: SELECT, WHERE, IN, BETWEEN, LIKE, NULLs, sorting, DISTINCT and data types
  • Aggregation: COUNT, SUM, AVG, GROUP BY, HAVING, CASE WHEN, dates, text functions and pivot-style reports
  • Joins: INNER, LEFT, FULL and SELF joins, UNION, subqueries, and how to avoid wrong totals from fan-out
  • Advanced SQL: CTEs, window functions (ROW_NUMBER, RANK, LAG, running totals, moving averages), safe data changes, views and indexes
  • SQL at work: AOV, repeat rate, conversion, cohorts, funnels, cleaning messy data, Excel and Power BI, checking AI-written SQL, interview patterns and a GitHub portfolio

Learn by doing. You follow Kabir, a fresher data analyst at QuickKart, a fictional 10-minute grocery app in eight Indian cities. Managers send him real business questions, and he answers them with SQL. Every query you see on screen is actually run on the QuickKart database, and the real results are shown. Wherever MySQL works differently from PostgreSQL, the difference is shown and tested. Every lesson has a practice file with checked answers, every module ends with notes and a self-assessment task, and two live projects (a business health report, and a retention and funnel study) give you portfolio work you can show employers.

Who this course is for. College students and freshers aiming for data analyst roles; working professionals in operations, marketing, finance or product who want to answer their own data questions; Excel users who want to work with bigger data; and anyone preparing for SQL interviews. No coding experience is needed.

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Overview

What you'll learn

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Write clean SQL queries to filter, sort and summarise data

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Join several tables without getting wrong totals

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Use CTEs and window functions for rankings and trends

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Calculate business metrics like AOV, repeat rate and conversion

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Build retention cohorts and funnel analyses

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Clean messy data and connect SQL to Excel and Power BI

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Check AI-written SQL before trusting it

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Answer common SQL interview questions and build a portfolio

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Curriculum

52 Lessons · 13:42:37 Hours

  • Why SQL? The Analyst's Most Asked-For Skill 100:19:10
  • How Databases Work: Tables, Rows, Columns and Data Types 100:15:53
  • Keys and Relationships: Primary Keys, Foreign Keys and the QuickKart Schema 100:15:48
  • Setting Up Your SQL Workspace: PostgreSQL, pgAdmin and a Browser Playground 100:16:21
  • Loading the QuickKart Database: Running a .sql Script and Importing CSVs 200:15:43
  • Your First Query: SELECT, FROM and the Results Grid 100:15:37
  • How SQL Thinks: Writing Order vs Running Order, and Reading Error Messages 100:15:31
  • SQL Dialects: PostgreSQL, MySQL, SQLite and Cloud Warehouses 100:17:04
  • NotesNotes
  • Self AssessmentTask
  • Choosing Columns: SELECT, Aliases and Calculated Columns 100:16:54
  • Filtering Rows with WHERE: Comparison and Logical Operators 100:16:06
  • Smarter Filters: IN, BETWEEN and LIKE 100:15:45
  • NULL: The Missing Value That Breaks Queries (IS NULL, COALESCE) 100:15:07
  • Sorting and Limiting: ORDER BY, LIMIT and Top-N Lists 100:16:00
  • DISTINCT and Counting Unique Values 100:16:20
  • Data Types in Practice: Casting Text, Numbers and Dates 100:17:06
  • Kabir's First Brief: Answering 10 Manager Questions 100:16:11
  • NotesNotes
  • Self AssessmentTask
  • Aggregate Functions: COUNT, SUM, AVG, MIN and MAX 100:16:03
  • GROUP BY: Summaries by City, Store and Category 100:15:25
  • WHERE vs HAVING: Filtering Rows and Filtering Groups 100:16:01
  • CASE WHEN: Building Your Own Categories 100:15:31
  • Working with Dates: EXTRACT, DATE_TRUNC and Date Maths 100:15:31
  • String Functions: Cleaning Names, Phones and Codes 100:16:02
  • Conditional Aggregation: Pivot-Style Reports in SQL 100:16:00
  • Kabir's Weekly Sales Report for the City Heads 100:15:30
  • SQL Cheat SheetFile
  • NotesNotes
  • Self AssessmentTask
  • Why Data Lives in Many Tables 100:15:26
  • INNER JOIN: Matching Orders to Customers 100:15:43
  • LEFT and RIGHT JOIN: Finding What's Missing 100:15:21
  • FULL OUTER, CROSS and SELF JOIN 100:15:32
  • Joining Three or More Tables 100:15:33
  • UNION, UNION ALL, INTERSECT and EXCEPT 100:15:16
  • Subqueries: In WHERE, FROM and SELECT 100:15:46
  • Common Join Mistakes: Duplicates, Fan-Out and Wrong Totals 100:15:42
  • NotesNotes
  • Self AssessmentTask
  • CTEs: Readable Queries with WITH 100:15:39
  • Window Functions I: OVER, PARTITION BY and ROW_NUMBER 100:15:35
  • Window Functions II: RANK, DENSE_RANK and Top-N per Group 100:15:07
  • Window Functions III: LAG, LEAD, Running Totals and Moving Averages 100:15:16
  • Advanced Patterns: Removing Duplicates, Finding Gaps and Latest Records 100:15:17
  • Creating and Changing Tables Safely: CREATE, INSERT, UPDATE, DELETE and Transactions 100:15:46
  • Views: Saving Queries Your Team Can Reuse 100:15:19
  • Indexes and Query Speed: Reading EXPLAIN Like an Analyst 100:15:31
  • SQL Cheat SheetFile
  • NotesNotes
  • Self AssessmentTask
  • Business Metrics in SQL: AOV, Repeat Rate and Conversion 100:15:44
  • Retention and Cohort Analysis 100:15:13
  • Funnel Analysis: From App Open to Order Delivered 100:15:19
  • Cleaning Messy Data with SQL 100:16:03
  • From SQL to Excel and Power BI: Exporting and Connecting 100:16:01
  • Using AI Assistants to Write and Check SQL, Safely 100:15:31
  • SQL Interview Questions: 20 Patterns That Keep Coming Up 200:16:01
  • Building a SQL Portfolio on GitHub 100:15:42
  • NotesNotes
  • Self AssessmentTask
  • Project 1, Part 1: QuickKart Business Health Report: Scoping 15 Questions 200:16:08
  • Project 1, Part 2: Answering, Checking and Presenting the 15 Questions 200:15:50
  • Project 2, Part 1: Cohort and Retention Analysis with Window Functions 200:15:19
  • Project 2, Part 2: Funnel Analysis and the 1-Page Insight Summary 200:15:18
Video LecturesWatch & rewatch anytime
Best Interactive ContentQuizzes and activities that stick
GuidanceAsk doubts, get expert answers
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Why learn SQL?

01

SQL appears in most data analyst job descriptions

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It works across PostgreSQL, MySQL, SQLite and cloud warehouses

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It lets you answer questions on data too big for Excel

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One query can be re-run every week, instead of repeating manual steps

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It's the foundation for Power BI, Python and data science

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It's a skill you can show quickly, through projects and interviews

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Who this course is for:

01

College students and freshers preparing for data analyst roles

02

Working professionals in operations, marketing, finance or product who want to answer their own data questions

03

Excel users who want to work with data too big for spreadsheets

04

Anyone preparing for SQL interview rounds

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Analysts who know basic SQL and want to learn window functions, cohorts and funnels

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Complete beginners, since no coding experience is needed

₹1999