How do you become a data analyst? Learn the core tools in order: spreadsheets, then SQL, then a BI tool (Power BI or Tableau), then Python basics. Build two or three portfolio projects on real data that answer business questions. Then apply for entry-level or internal analyst roles. Most career changers studying 8–10 hours a week become job-ready in about 6–12 months, and a degree is helpful but not required.

This is the pillar guide in Tutopiya’s data and AI series. Each step links to a deeper guide.

Key takeaways

• SQL is the single most important skill for entry-level analyst jobs.
• Employers hire on evidence, so your portfolio matters more than any certificate.
• Communication is half the job: turning numbers into a decision someone can act on.
• An internal move (becoming the “data person” in your current team) is often the fastest route.

What does a data analyst do?

A data analyst turns raw data into answers. On a typical day you might:

• Write SQL to pull sales, customer or operations data
• Clean messy data and combine sources
• Build or update dashboards
• Investigate a question such as “Why did sign-ups drop last week?”
• Present findings with a clear recommendation

It sits between the business and the data. If you’re curious how it differs from neighbouring roles, see data analyst vs data scientist and business analyst vs data analyst.

The data analyst roadmap, step by step

Step	Learn	Rough time (8–10 hrs/week)	Proof you’ve got it
1	Spreadsheets: lookups, pivot tables, charts	3–4 weeks	Clean and summarise a messy dataset
2	SQL: SELECT, JOINs, GROUP BY, window functions	6–8 weeks	Answer 20 business questions on a sample database
3	BI tool: Power BI or Tableau	4–6 weeks	A published, interactive dashboard
4	Statistics basics: averages, distributions, A/B tests	3–4 weeks	Explain whether a change is significant
5	Python (pandas) basics	6–8 weeks	Automate one cleaning or reporting task
6	Portfolio and storytelling	ongoing	2–3 projects with written findings

Step 1: spreadsheets

Most business data still lives in Excel or Google Sheets. Master XLOOKUP, pivot tables, conditional formatting and charts. See Python vs Excel for data analysis for when each tool fits.

Step 2: SQL, the non-negotiable

Nearly every analyst job description lists SQL. Learn to filter, join, aggregate and use window functions. Start with our SQL for data analysis guide.

Step 3: a BI tool

Dashboards are how most analysts’ work is consumed. Pick one tool, Power BI or Tableau, based on what employers in your market use (Power BI vs Tableau). If you choose Power BI, Microsoft’s PL-300 certification is a recognised credential.

Step 4: enough statistics

You don’t need a maths degree. You need to understand averages and medians, spread, correlation versus causation, and the basics of A/B testing.

Step 5: Python basics

Python (with pandas) handles data too big or messy for spreadsheets and automates repetitive reports. It’s increasingly listed, but it comes after SQL.

Step 6: portfolio and storytelling

Two or three strong projects beat ten tutorials. Each one should start with a question, use real data, and end with a recommendation. See data analyst portfolio projects for ideas and a structure.

For the full list of what employers ask for, see data analyst skills.

Do you need a certificate?

Certificates help structure learning and get you past some CV filters, but they don’t replace evidence. Our honest take is in is a data analytics certificate worth it?

How to land your first data analyst role

1. Look inside your current employer first. Offer to build the report your team keeps asking for. Internal moves skip the “no experience” problem.
2. Target analyst-adjacent titles: reporting analyst, operations analyst, marketing analyst, junior BI analyst.
3. Tailor your CV to outcomes: “Built a dashboard that cut weekly reporting from 4 hours to 20 minutes.”
4. Prepare for a SQL test and a case study. Most interview processes include both.
5. Write about your projects on LinkedIn or a simple portfolio site. Hiring managers do look.

Where AI fits

Generative AI is changing analyst work. It drafts SQL, explains code and summarises results, but it doesn’t replace the judgement of knowing which question to ask and whether an answer is right. Learn the fundamentals first, then use AI to go faster. See how to use generative AI at work, prompt engineering basics, the machine learning roadmap and AI jobs without coding.

Learn it live, with a mentor

Self-study works for some people, and many stall around SQL joins or their first portfolio project. Tutopiya is planning a 12-week live Data Analytics with Python & SQL cohort: small groups, a practising analyst as mentor, weekly marked assignments and a graded capstone project. It isn’t running yet. Register interest in the data analytics programme. Nothing is charged, and it opens if enough people want it.

Sources

• Microsoft Learn: Power BI Data Analyst (PL-300)
• Mode: SQL tutorial for data analysis
• pandas: official getting started guide

Frequently asked questions

Can I become a data analyst without a degree? +

Yes. Many employers hire analysts on demonstrated skill. A portfolio of two or three real projects using SQL, a BI tool and spreadsheets, plus the ability to explain your findings, can outweigh the lack of a degree, especially for entry-level and internal-transfer roles.

How long does it take to become a data analyst? +

Most career changers who study 8 to 10 hours a week need about 6 to 12 months to become job-ready: around three months on core skills, then projects, a portfolio and applications. People who already use spreadsheets at work often move faster.

Do data analysts need to know Python? +

Not always. Many entry-level analyst roles require SQL, Excel and a BI tool such as Power BI or Tableau. Python is increasingly asked for and helps with automation and larger datasets, but SQL comes first.

Is data analytics hard to learn? +

The individual skills are learnable by most people with basic numeracy. The hard parts are persistence and learning to ask good business questions, not advanced mathematics.

What does a data analyst actually do day to day? +

Pull data with SQL, clean and combine it, build reports and dashboards, answer questions from managers, investigate why a metric moved, and present findings with clear recommendations.

Founding cohorts · nothing charged

Want to learn this live, with a mentor?

Tutopiya is planning small, mentor-led online cohorts in English test prep, data & AI, business & finance and digital careers. Tell us which one you want. The programmes with the most interest open first, and the people on the waitlist hear about them first.

See the planned programmes