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πŸ“Š Data Analyst Roadmap (2025)

Master the Skills That Top Companies Are Hiring For!

πŸ“ 1. Learn Excel / Google Sheets
Basic formulas & formatting
VLOOKUP, Pivot Tables, Charts
Data cleaning & conditional formatting

πŸ“ 2. Master SQL
SELECT, WHERE, ORDER BY
JOINs (INNER, LEFT, RIGHT)
GROUP BY, HAVING, LIMIT
Subqueries, CTEs, Window Functions

πŸ“ 3. Learn Data Visualization Tools
Power BI / Tableau (choose one)
Charts, filters, slicers
Dashboards & storytelling

πŸ“ 4. Get Comfortable with Statistics
Mean, Median, Mode, Std Dev
Probability basics
A/B Testing, Hypothesis Testing
Correlation & Regression

πŸ“ 5. Learn Python for Data Analysis (Optional but Powerful)
Pandas & NumPy for data handling
Seaborn, Matplotlib for visuals
Jupyter Notebooks for analysis

πŸ“ 6. Data Cleaning & Wrangling
Handle missing values
Fix data types, remove duplicates
Text processing & date formatting

πŸ“ 7. Understand Business Metrics
KPIs: Revenue, Churn, CAC, LTV
Think like a business analyst
Deliver actionable insights

πŸ“ 8. Communication & Storytelling
Present insights with clarity
Simplify complex data
Speak the language of stakeholders

πŸ“ 9. Version Control (Git & GitHub)
Track your projects
Build a data portfolio
Collaborate with the community

πŸ“ 10. Interview & Resume Preparation
Excel, SQL, case-based questions
Mock interviews + real projects
Resume with measurable achievements

✨ React ❀️ for more



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πŸ“Š Data Analyst Roadmap (2025)

Master the Skills That Top Companies Are Hiring For!

πŸ“ 1. Learn Excel / Google Sheets
Basic formulas & formatting
VLOOKUP, Pivot Tables, Charts
Data cleaning & conditional formatting

πŸ“ 2. Master SQL
SELECT, WHERE, ORDER BY
JOINs (INNER, LEFT, RIGHT)
GROUP BY, HAVING, LIMIT
Subqueries, CTEs, Window Functions

πŸ“ 3. Learn Data Visualization Tools
Power BI / Tableau (choose one)
Charts, filters, slicers
Dashboards & storytelling

πŸ“ 4. Get Comfortable with Statistics
Mean, Median, Mode, Std Dev
Probability basics
A/B Testing, Hypothesis Testing
Correlation & Regression

πŸ“ 5. Learn Python for Data Analysis (Optional but Powerful)
Pandas & NumPy for data handling
Seaborn, Matplotlib for visuals
Jupyter Notebooks for analysis

πŸ“ 6. Data Cleaning & Wrangling
Handle missing values
Fix data types, remove duplicates
Text processing & date formatting

πŸ“ 7. Understand Business Metrics
KPIs: Revenue, Churn, CAC, LTV
Think like a business analyst
Deliver actionable insights

πŸ“ 8. Communication & Storytelling
Present insights with clarity
Simplify complex data
Speak the language of stakeholders

πŸ“ 9. Version Control (Git & GitHub)
Track your projects
Build a data portfolio
Collaborate with the community

πŸ“ 10. Interview & Resume Preparation
Excel, SQL, case-based questions
Mock interviews + real projects
Resume with measurable achievements

✨ React ❀️ for more

BY Python for Data Analysts


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The seemingly negative pandemic effects and resource/product shortages are encouraging and allowing organizations to innovate and change.The news of cash-rich organizations getting ready for the post-Covid growth economy is a sign of more than capital spending plans. Cash provides a cushion for risk-taking and a tool for growth.

The STAR Market, as is implied by the name, is heavily geared toward smaller innovative tech companies, in particular those engaged in strategically important fields, such as biopharmaceuticals, 5G technology, semiconductors, and new energy. The STAR Market currently has 340 listed securities. The STAR Market is seen as important for China’s high-tech and emerging industries, providing a space for smaller companies to raise capital in China. This is especially significant for technology companies that may be viewed with suspicion on overseas stock exchanges.

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