Data Analyst
A data analyst answers business questions with data: SQL to get it, Python or spreadsheets to shape it, and dashboards to share it.
- Write SQL to pull and combine data
- Clean data and check it makes sense
- Build dashboards and reports
- Explain what the numbers mean to the team
- SQL analyses with joins and window functions
- A cleaned dataset in Python
- A dashboard that answers a real question
Where it leads: Senior analyst, analytics engineer, or data scientist.
Every skill, at the level the job needs
Updating… · change the level or company to see how it shifts
data-analyst
core- Data science
- Key Concepts of Data
- Collections
- Cleanup
- Exploration
- Visualization
sql
core- Relational DB theory
- Relational Data Model
- RDBMS Benefits and Limitations
- SQL and Databases
- NoSQL DBs
- Basics SQL
git-github
core- git init
- What is Version Control?
- Why use Version Control?
- git config
- Local vs Global Config
- Git
datastructures-and-algorithms
core- Language Syntax
- Control Structures
- Python
- Pseudocode
- Pseudocode basics
- Functions
What the levels mean
- L1 · AwareKnows what it is and when it's used
- L2 · BasicsCan use it with guidance
- L3 · WorkingUses it independently on the job
- L4 · StrongHandles hard cases, reviews others
- L5 · ExpertDesigns with it, teaches it
Interviews, by kind of company
Your route adds an interview track that matches the company you choose.
Large IT services firms: aptitude, fundamentals, technical and HR rounds.
Online assessment, coding rounds, a design round.
Hard timed coding rounds, system design, behavioural interviews.
Questions
What does a Data Analyst need to know?
Data Analyst Roadmap, SQL Roadmap at a working level, plus BI Analyst, Python Developer. The skills section above lists every one with its level.
How long does it take to become a Data Analyst?
About 165 hours of study from scratch. At 10 hours a week that's roughly 17 weeks; anything you already know is skipped after the readiness test.
I already know some of this. Do I start from zero?
No. The optional readiness test finds what you already know and your route skips it.
Does the route change for product companies or senior roles?
Yes. Choose your level and the kind of company above: the skills and target levels adjust, for example deeper data structures and system design for product companies.
Other roles in the Data & AI track
They share many skills with this one, so progress carries over if you switch.
Models and analyses with Python and machine learning.
Pipelines and data platforms.
Applications built on AI models: assistants, agents, AI features.
Deploy and run machine-learning systems in production.