Career Path

Data Analyst

Turn raw data into decisions that move businesses forward

Data Analysts are the most accessible entry point into data careers. They clean, analyze, and visualize data to help businesses make smarter decisions. In 2026, AI tools handle much of the grunt work — but SQL is still king, and the ability to ask the right questions of data is more valuable than ever. Every company with data needs analysts, and that's every company.

What you'd do day-to-day

  • Writing SQL queries to pull and analyze data
  • Building dashboards in Tableau, Looker, or Power BI
  • Creating reports for leadership and business teams
  • Identifying trends and anomalies in business metrics

Who hires for this role

  • Retail and e-commerce companies
  • Marketing agencies and ad tech
  • Healthcare systems
  • Virtually any mid-to-large company
Scroll to explore

Salary Progression

Entry

$55K

Mid

$85K

Senior

$130K+

Time to hire

4-8 months (focused study)

Est. cost

$0-$500 (self-study)

Your Roadmap

How to become an Data Analyst

Step by step, from where you are now to getting hired.

1

Spreadsheets + SQL Foundations

2-3 months

Start with Excel/Google Sheets for data thinking, then learn SQL immediately. SQL is tested in every data analyst interview and used every single day on the job. This is the foundation everything else builds on — don't rush it.

Excel/Google SheetsSQL (SELECT, JOIN, GROUP BY, subqueries)Data types & schemasBasic data cleaningDatabase concepts

Potential salary at this stage

$55K

2

Data Visualization (Tableau + Power BI)

2-3 months

Knowing SQL gets you data. Visualization is how you make it mean something to people who don't speak SQL. Learn Tableau (most common in job postings) and at least basic Power BI. Dashboards that tell a story are what get you hired.

TableauPower BI basicsDashboard designData storytellingChart selection

Potential salary at this stage

$55K

3

Python for Data Analysis

2-3 months

Python is how you level up from 'analyst' to 'analyst who automates things.' Learn Pandas for data manipulation, Matplotlib/Seaborn for visualization, and basic scripting. In 2026, AI coding assistants make Python much more accessible — but you still need to understand what the code is doing.

Python basicsPandasMatplotlib/SeabornJupyter NotebooksData cleaning with code

Potential salary at this stage

$85K

4

Statistics + Business Context

1-2 months

The difference between a junior and mid-level analyst is statistical thinking. Learn hypothesis testing, correlation vs causation, confidence intervals, and A/B testing. More importantly, learn to connect data insights to business outcomes — 'revenue went up 12%' matters more than 'p < 0.05'.

Descriptive statisticsHypothesis testingA/B testingCorrelation vs causationBusiness metrics (KPIs, cohorts, funnels)

Potential salary at this stage

$85K

5

Portfolio + Certification

1-2 months

Build 3-5 analysis projects on real datasets and publish them. Use Kaggle datasets, government open data, or scrape your own. Each project should show: question → data cleaning → analysis → visualization → insight. The Google Data Analytics cert from step 1 plus a strong portfolio will get you interviews.

Portfolio projectsGitHub for data projectsKagglePresentation skillsInterview prep

Potential salary at this stage

$130K+

Certifications that boost this career

Google Data Analytics Professional Certificate

Best entry cert — employer consortium of 150+ companies

See how it helps

Tableau Desktop Specialist / Data Analyst

+$8K salary — most requested viz tool

Explore this cert

Microsoft PL-300 Power BI Data Analyst

+$10K salary — dominant in enterprise

Learn more

Google Advanced Data Analytics Certificate

Bridge to senior analyst / junior data scientist

View details