What does a data analyst do day-to-day?

Writing SQL queries to extract and transform data, building dashboards and reports, answering ad-hoc business questions, presenting findings to stakeholders, and maintaining data models. It's mostly SQL and spreadsheets at most companies.

How long does it take to become a data analyst?

2–6 months of focused study is enough to qualify for entry-level roles if you have a relevant degree. Starting from scratch (non-technical background + no degree), plan for 6–12 months to build the SQL, Python, and portfolio skills needed.

Is data analyst a stepping stone to data science?

It's the most common path. Many data scientists started as analysts, built Python and ML skills on the side, then transitioned. The advantage is you earn while you learn and develop deep business domain knowledge.

Do data analysts need to know statistics?

Yes — basic statistics (mean, median, variance, distributions, p-values, A/B testing) are expected. You don't need advanced statistics for most analyst roles, but you do need to know when to use each method and how to explain results without misrepresenting them.

Step-by-Step Guide

How to Become a Data Analyst

Business, statistics, economics, or CS degree; bootcamps and certificates work too

First job in 2–8 months

Median $85K/yr

+23% job growth

Salary range

$55K – $130K+

Job growth

+23%

Time to first role

2–8 months

Education

Business, statistics, economics, or CS degree

Step-by-step roadmap to your first Data Analyst role

Master SQL and Excel/Sheets

1–2 months

SQL is the #1 required skill in data analyst job postings. Excel and Google Sheets are required for business analysis. Master JOINs, aggregations, window functions, and pivot tables before anything else.

Learn a visualisation tool

1–2 months

Tableau or Power BI are the enterprise standards. Looker is common at SaaS companies. Google Data Studio is free and widely used. Build 2–3 dashboards from public datasets to show on your portfolio.

Learn Python or R for analysis

2–3 months

Python (pandas, matplotlib) is the more versatile choice. R is preferred in academia and statistics-heavy roles. Python proficiency moves you from analyst to senior analyst or data scientist more easily.

Build a portfolio of analysis projects

2–3 months

Choose real business questions from public datasets. Kaggle, Data.gov, and Google BigQuery public datasets are all good sources. Present findings as if to a business audience — key insights, not just charts.

Earn a Google Data Analytics Certificate

3–6 months

The Google Data Analytics Certificate (Coursera) is widely respected by hiring managers, covers SQL and Tableau, and is achievable part-time. It's one of the best return-on-investment credentials in the data field.

Is Data Analyst actually the right fit for you?

The 60-second Career Fit Quiz scores you against all 46 career paths — including Data Analyst — based on your actual skills and goals.

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Core skills for a Data Analyst

8 key skills expected by hiring managers.

SQLExcel & Google SheetsData visualizationPython basicsStatistics fundamentalsDashboard buildingA/B testing conceptsBusiness communication

Top certifications to get hired faster

Google Data Analytics Professional Certificate

Issued by Google / Coursera

#1 pick

Microsoft Power BI Data Analyst Associate (PL-300)

Issued by Microsoft

#2 pick

Tableau Desktop Specialist

Issued by Tableau / Salesforce

#3 pick

Backgrounds that transition well into Data Analyst

Finance analystMarketing coordinatorOperations coordinatorScience graduate

Job titles to target first

Search for these when applying — they're the standard entry-level titles that lead to Data Analyst roles.

Junior Data Analyst

Business Intelligence Analyst

Reporting Analyst

Frequently asked questions about becoming a Data Analyst

Other Data & Analytics careers to explore

Data Scientist

Median $115K/yr · +35% growth

Machine Learning Engineer

Median $145K/yr · +40% growth

Full Data Analyst career profile Calculate Data Analyst salary jump

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