Free Learning Roadmap

How to Become a Data Analyst

Turns data into decisions. SQL, spreadsheets, BI tools, and clear storytelling. Entry point for most modern data careers.

Topics
11
Resources
34
Cost
Free
Most resources are free or freemium
Format
Self-paced

1. SQL

core
SQL Fundamentals

SELECT, WHERE, GROUP BY, JOIN. The bread and butter — must be second nature.

Advanced SQL

Window functions, CTEs, subqueries, self-joins. The difference between a junior and senior analyst.

Query Performance Basics

Reading EXPLAIN plans, indexes, avoiding cartesian joins. Enough to not lock the warehouse.

2. Spreadsheets

core
Excel / Google Sheets Mastery

Pivot tables, VLOOKUP/XLOOKUP, INDEX/MATCH, arrays, dynamic ranges. Still the daily interface for most business users.

3. BI & Visualisation Tools

core
Tableau

The enterprise-default BI tool. Calculated fields, LOD expressions, dashboard actions.

Power BI

Microsoft-shop default. DAX language, Power Query, data modelling.

Looker, Metabase, Superset

Modern BI options. Metabase for the SMB tier, Looker/LookML for governed enterprise, Superset for open source.

4. Statistics

core
Descriptive Statistics

Mean vs median, variance, percentiles, distributions. The base layer for any interpretation.

Significance & A/B Analysis

P-values, confidence intervals, sample size. Enough to not overclaim from a small experiment.

5. Data Modelling

core
Warehouse & Modelling Basics

Fact vs dimension, star vs snowflake schema. Even if you don't build them, understanding models saves hours of guessing.

dbt for Analysts

SQL-native modelling tool. Analyst-engineer bridge role increasingly requires this.

6. Python or R for Analytics

recommended
Python + pandas

For analyses that outgrow SQL. pandas, matplotlib, seaborn. Notebook fluency.

R + tidyverse

Preferred in stats-heavy fields (biotech, econ, academic). ggplot is still the gold standard for statistical viz.

7. Visualisation Craft

core
Chart Choice & Design

Bars vs lines vs scatter — the choice reveals or hides the pattern. Tufte, Wilke, Cairo as reference.

Dashboard Design

One question per dashboard, hierarchy of information, actionable defaults. Less is almost always more.

8. Storytelling & Business Communication

core
Storytelling with Data

Executives don't read dashboards. They read a headline, one chart, and one recommendation.

9. Domain Depth

recommended
Pick a Vertical

Product analytics, marketing analytics, finance analytics, ops analytics. Depth in one beats surface breadth in five.

10. Engineering-Adjacent

recommended
Git Basics

For dbt projects, notebooks, collaborative SQL work. Enough git and PR fluency to work with engineering.

11. Career

optional
Analyst Voices

Where working analysts talk shop.

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Curated by WhatTNext Ai · methodology · all roadmaps · last updated 2026-07-29