Data · Stable
Data Analyst: Skills, Projects & Interview Questions (2026)
Analyze data and build dashboards that answer business questions and drive action.
What a Data Analyst actually does
Querying data, building dashboards, and answering business questions for stakeholders.
Top hiring companies: Amazon, Flipkart, Deloitte, Accenture, Walmart, Swiggy.
Top industries: All industries, Retail, Finance, Tech, Healthcare.
Skills you need to become a Data Analyst
| Skill | Importance | Learning hours | Interview weight |
|---|---|---|---|
| SQL | 10/10 | ~40h | High |
| Excel | 9/10 | ~30h | High |
| Data Visualization | 9/10 | ~30h | High |
| Power BI / Tableau | 9/10 | ~40h | High |
| Python (Pandas) | 8/10 | ~50h | Medium |
| Statistics | 8/10 | ~40h | High |
| Data Cleaning | 8/10 | ~30h | High |
| Business Acumen | 8/10 | ~20h | High |
| Dashboarding | 8/10 | ~30h | Medium |
| Storytelling with Data | 7/10 | ~20h | Medium |
Core tools: Excel, Power BI, Tableau, SQL Workbench, Python (Pandas), Google Sheets.
Data Analyst learning roadmap
Beginner · 2-3 months
Foundations & core tooling
Build: Build a SQL + Excel report answering 5 business questions from a raw dataset.
Intermediate · 3-4 months
Applied, real-world builds
Build: Create an interactive Power BI/Tableau dashboard with cleaned data and KPIs.
Advanced · 3-4 months
Production, scale & specialization
Build: Deliver a stakeholder-ready analytics story: cohort/funnel analysis with recommendations.
10 Data Analyst portfolio projects
SQL Business Report
BeginnerAnswer business questions from a raw dataset in SQL.
Skills: SQL, Data Cleaning, Excel
Excel Sales Dashboard
BeginnerInteractive Excel dashboard with PivotTables.
Skills: Excel, Data Visualization
Power BI Sales Dashboard
BeginnerCleaned data + KPI dashboard in Power BI.
Skills: Power BI, Data Visualization, SQL
Cohort & Funnel Analysis
IntermediateAnalyze retention and conversion with SQL.
Skills: SQL, Statistics, Data Visualization
Tableau Story Dashboard
IntermediateStakeholder-ready Tableau storytelling dashboard.
Skills: Tableau, Data Visualization, SQL
Python EDA Report
IntermediateExploratory analysis and insights with pandas.
Skills: Python, Data Cleaning, Statistics
KPI Tracking System
IntermediateAutomated KPI report from a live source.
Skills: SQL, Power BI, Data Visualization
Marketing Performance Analysis
IntermediateAnalyze campaign performance and recommend.
Skills: SQL, Excel, Data Visualization
Sales Forecasting (Analyst)
IntermediateSimple forecast with trend analysis.
Skills: Excel, Statistics, Data Visualization
Customer Behavior Deep-dive
AdvancedEnd-to-end analysis with segmentation and actions.
Skills: SQL, Statistics, Data Visualization
Common Data Analyst interview questions
Find the second-highest salary in a table.Medium
What they're testing: DENSE_RANK or a correlated subquery / OFFSET
How do you clean messy data in Excel?Medium
What they're testing: Text functions, dedup, validation
How do you visualize for non-technical stakeholders?Medium
What they're testing: Lead with the insight; reduce cognitive load
Difference between deepcopy and shallow copy.Medium
What they're testing: Nested references copied vs shared
Difference between correlation and causation.Easy
What they're testing: Association vs cause; confounders, need experiments
What are window functions? Give a use case.Medium
What they're testing: Compute over a partition without collapsing rows; running totals, ranks
Useful functions for analysts.Medium
What they're testing: SUMIFS, COUNTIFS, IF, TEXT
When is a table better than a chart?Easy
What they're testing: Precise lookups/few values
How does exception handling work? try/except/finally.Easy
What they're testing: Catch specific exceptions; finally always runs
Explain precision and recall and the trade-off.Medium
What they're testing: TP/(TP+FP) vs TP/(TP+FN); threshold tunes balance
Difference between RANK, DENSE_RANK and ROW_NUMBER.Medium
What they're testing: Tie handling: gaps vs no gaps vs always-unique
VLOOKUP vs INDEX-MATCH vs XLOOKUP.Easy
What they're testing: Lookup approaches and their limits
Certifications for Data Analysts
- Microsoft Certified: Power BI Data Analyst Associate (PL-300)Microsoft · Very High value
- Google Data Analytics Professional Certificate (Coursera)Google · High value
- Tableau Desktop SpecialistTableau (Salesforce) · High value
Data Analyst career path
Data Analyst -> Senior Analyst -> Analytics Manager / Data Scientist
Common moves into this role / from here:
- → Data Engineer (6-9 months) — close: Python, PySpark/Spark, ETL/ELT, data warehousing, Airflow, cloud platforms
- → Product Analyst (3-4 months) — close: Product metrics, A/B testing, funnel/cohort analysis, product analytics tools
- → Data Scientist (6-9 months) — close: Statistics depth, ML algorithms, Python for ML, feature engineering, experimentation
- → Business Intelligence Developer (3-4 months) — close: Data warehousing, ETL tools, DAX, dimensional modeling, semantic models
Related roles: Product Analyst, Business Analyst, BI Developer
Frequently asked questions
What skills do you need to become a Data Analyst?
Core skills include SQL, Excel, Data Visualization, Power BI / Tableau, Python (Pandas). Turn analysis into a clear recommendation, not just a dashboard.
What projects should a Data Analyst build for a portfolio?
Strong starter projects: SQL Business Report; Excel Sales Dashboard; Power BI Sales Dashboard; Cohort & Funnel Analysis.
How long does it take to become job-ready as a Data Analyst?
A focused plan runs roughly 2-3 months for fundamentals, then applied projects. Difficulty rating: 4/10.
What is the career path for a Data Analyst?
Data Analyst -> Senior Analyst -> Analytics Manager / Data Scientist
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