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PR🚀 60-Day Data Analyst Roadmap (Practical-First Approach)
🎯 Goal:
2–3 strong projects
Portfolio + resume ready
Actively applying with proof of work
Phase 1: Foundation Through Practice (Day 1–15)
🔹 Focus: Learn by DOING (not watching)
Daily Structure (2–3 hrs max):
30 min → Learn concept
1.5 hr → Practice
30 min → Mini task
What to do:
✅ Excel (Days 1–5)
Functions: VLOOKUP, INDEX-MATCH, IF, COUNTIF
Pivot Tables
Cleaning messy data
👉 Practice:
Take any dataset → clean + create summary dashboard
✅ SQL (Days 6–10)
SELECT, WHERE, GROUP BY
JOINS (very important)
Basic aggregations
👉 Practice:
Solve 15–20 real queries daily
Use platforms like:
LeetCode (easy SQL)
✅ Mini Project 1 (Days 11–15)
Dataset: Sales / E-commerce / Netflix
👉 Do:
Clean data
Analyze trends
Write insights (THIS is key)
📌 Output:
1 clean project (Excel or SQL-based)
Phase 2: Real Projects + Storytelling (Day 16–35)
🔥 Focus: Portfolio > Learning
✅ Project 2 (Days 16–25) — Python + EDA
Use: Pandas + Matplotlib
👉 Steps:
Data cleaning
EDA (find patterns)
Ask business questions:
Why sales dropped?
Which segment performs best?
📌 Output:
Jupyter Notebook + insights
✅ Project 3 (Days 26–35) — Power BI / Dashboard
Build 1 STRONG dashboard
👉 Include:
KPIs
Filters
Business insights
📌 Important:
Don’t just build charts. Tell a story.
Phase 3: Proof of Work + Job Prep (Day 36–50)
🔥 Focus: Getting interview-ready
✅ Resume (Day 36–38)
Add:
Projects (impact-based)
Tools
Metrics
👉 Example:
❌ “Analyzed sales data”
✅ “Improved sales insights by identifying top 3 revenue drivers”
✅ Portfolio (Day 39–42)
GitHub (projects uploaded)
✅ Daily Routine (Day 43–50)
10 SQL questions daily
Revise projects
Practice explaining your work
👉 MOST IMPORTANT:
Be able to explain your project like a story
Phase 4: Aggressive Applications (Day 51–60)
🔥 Focus: Getting calls
✅ Apply Daily (Non-negotiable)
20–30 applications/day
Platforms:
LinkedIn
Naukri
Company websites
✅ Cold Messaging (Daily)
Message recruiters/employees:
“Hi, I’ve built projects in SQL, Python & Power BI. I’d love to be considered for entry-level roles.”
You don’t get hired by learning. You get hired by showing.
#dataanalyst
@prernaa.py
