Data analytics is one of the fastest-growing careers globally. Organisations in healthcare, finance, retail, government, telecoms, and technology depend on data analysts to turn raw data into insights for decision-making.
How to become a Data Analyst with no Experience
If you are starting in 2026, don’t try to learn everything at once. Build skills step by step, as each stage supports the next.
Step 1: Master Microsoft Excel
Excel is still one of the most widely used tools in analytics. It is fast, flexible, and ideal for early data exploration.
Key Skills
Data cleaning
- Remove duplicates
- Text to Columns
- Flash Fill
- TRIM, CLEAN, SUBSTITUTE
- Find & Replace
Functions
- IF, IFS
- SUMIFS, COUNTIFS
- XLOOKUP (preferred), VLOOKUP
- INDEX & MATCH
- FILTER, SORT, UNIQUE
Analysis tools
- Pivot Tables and Charts
- Slicers
- Conditional formatting
Visualisation
- Bar, line, pie charts
- Dashboards
Outcome
You should be able to answer:
- Top-selling products
- Budget vs actual performance
- Monthly trends
- High-performing employees
Step 2: Learn SQL
Excel has limits with large datasets. SQL allows you to query millions of rows quickly.
Core Skills
- SELECT, FROM, WHERE
- ORDER BY, LIMIT
- AND, OR, NOT, IN, BETWEEN, LIKE
- COUNT, SUM, AVG, MAX, MIN
- GROUP BY (by department, country, product, month)
Joins
- INNER JOIN
- LEFT JOIN
- RIGHT JOIN
- FULL OUTER JOIN
Practice Projects
- Customer orders
- Hospital records
- Employee data
- Retail sales
Step 3: Master Advanced SQL
This is where you start thinking like a professional analyst.
Key Topics
Window functions
- ROW_NUMBER, RANK, DENSE_RANK
- LAG, LEAD
CTEs (Common Table Expressions)
Improve readability and structure of complex queries.
Subqueries
- Nested and correlated queries
Advanced analysis
- Running totals
- Rolling averages
- Year-over-year comparisons
- Monthly growth
Case statements
Used for business rules, e.g.:
If Sales > £10,000 → “High Performer”
Business Questions
- Customers inactive for 6 months
- Most profitable products
- Underperforming stores
- Hospital waiting time breaches
Step 4: Learn Power BI
Power BI turns data into interactive dashboards and business insights.
Key Areas
Data import
- Excel, SQL, CSV, APIs, SharePoint
Power Query
- Clean, transform, merge data
Data modelling
- Relationships
- Star schema
- Fact and dimension tables
DAX
Start with:
- SUM, CALCULATE, FILTER
- ALL, DIVIDE, SWITCH
Then: - Time intelligence
- YoY analysis
- Running totals
Dashboards
Examples:
- Sales: revenue, trends, top products
- HR: turnover, recruitment, diversity
- Healthcare: waiting lists, occupancy
- Finance: budget vs actuals
Build a Portfolio
Employers hire problem-solvers, not just tool users.
Complete 8–10 projects across:
Healthcare, finance, retail, telecoms, HR, education, government, supply chain.
Each project should include:
- Problem statement
- Dataset
- Cleaning process
- Analysis
- Dashboard
- Insights
- Recommendations
Complementary Skills of a Data Analyst
- Data storytelling
- Critical thinking
- Business understanding
- Communication
- Problem-solving
- Attention to detail
- Report writing
Suggested Timeline
- Excel: 3–4 weeks
- SQL: 4–6 weeks
- Advanced SQL: 3–5 weeks
- Power BI: 5–7 weeks
- Portfolio: ongoing
With 8–10 hours weekly, you can become job-ready in 4–6 months.
Career Path to become a Data Anayst
- Data Analyst
- Senior Data Analyst
- BI Analyst
- Analytics Consultant
- Analytics Manager
- Data Scientist
- Head of Analytics
Final Advice
Focus on depth, not tools overload. Master Excel, SQL, Advanced SQL, and Power BI first. Build real-world projects and document your work clearly. A strong portfolio plus consistency will make you stand out in the data analytics job market.
Apply here for : Data analyst entry and senior level Roles