Foundation Skills for Data Careers:
- Excel and spreadsheet analysis
- SQL queries, joins and aggregations
- Python syntax and data structures
- Descriptive statistics and probability
- Data cleaning and documentation
- Clear written and verbal communication

SQL Basics for Analytics:
- SELECT, FROM, WHERE
- JOINs (INNER, LEFT, RIGHT)
- GROUP BY and HAVING
- ORDER BY
- Aggregate functions (SUM, AVG, COUNT)
- Subqueries
- CTEs (Common Table Expressions)
- Window functions
- Date/time functions
- String functions

Data Analyst Skills for Arts Graduates:
- SQL and dashboard design
- KPI definitions and data storytelling
- Power BI or Tableau
- Basic Python and statistics
- Stakeholder communication
- Portfolio case studies

Interview Skills:
- Explain your project step by step
- Convert business questions into metrics
- Discuss data cleaning decisions
- Explain charts without jargon
- Answer basic SQL and Excel questions
- Show curiosity and structured thinking

Every Data Analyst Project Should Include:
1. Business question and dataset source
2. Data cleaning steps
3. SQL queries or spreadsheet logic
4. Dashboard or visual analysis
5. Three to five written insights
6. Practical recommendations

Portfolio Checklist:
- One Excel project
- One SQL case study
- One Power BI dashboard
- One domain project related to your Arts background
- GitHub or shareable project folder
- One-page resume with project impact

Data Analyst Learning Timeline:

Month 1: Excel and Data Basics
- Formulas, Pivot Tables and charts
- Cleaning and sorting datasets
- Understand rows, columns and KPIs

Months 2-3: SQL Fundamentals
- SELECT, WHERE, JOIN and GROUP BY
- Practice with business questions
- Write and explain queries

Months 4-5: Power BI and Projects
- Build two interactive dashboards
- Write insights and recommendations
- Publish your portfolio

Months 6-8: Job Preparation
- Resume and LinkedIn optimization
- SQL, Excel and case-study practice
- Targeted applications and networking

Job Preparation Guide:

Target Roles:
Junior Data Analyst | MIS Analyst | Reporting Analyst

Resume Keywords:
Excel | SQL | Power BI | Data Cleaning | Data Visualization

Interview Topics:
Joins | Aggregations | Pivot Tables | KPIs | Dashboard Insights

Portfolio Proof:
Two dashboards | One SQL case study | Clear recommendations

Helpful Certifications:
- Google Data Analytics Professional Certificate
- Microsoft PL-300 after dashboard practice

Data Analyst Job Search Plan:

Month 1: Excel Mastery
- Formulas, pivot tables, charts
- Data cleaning and formatting
- What-if analysis

Month 2: SQL Fundamentals
- SELECT, JOINs, GROUP BY
- Subqueries and CTEs
- Practice on real datasets

Month 3: SQL Practice
- Connect to data sources
- Build dashboards and reports
- Publish and share

Month 4: Power BI Dashboard
- Build 3 portfolio dashboards
- Use real-world datasets
- Document and share on GitHub

Month 5: Portfolio Projects
- Pandas for data manipulation
- Matplotlib for visualization
- Basic machine learning

Month 6: Resume and Applications
- Resume and portfolio
- Interview preparation
- Networking and applications

Recommended Resources:

Free Resources:
- Microsoft Learn – Power BI
- Google Data Analytics (Coursera)
- W3Schools – SQL and Excel
- Kaggle – Datasets and notebooks
- YouTube – Analytics channels

Paid Resources:
- Uncodemy – Data Analytics Training Course
- DataCamp – Analytics tracks
- Coursera – Specializations
- LinkedIn Learning – BI courses

Certifications (Recommended):
- Microsoft PL-300 (Power BI)
- Tableau Desktop Specialist
- Google Data Analytics Professional