📁 STEP 16 — Build a Portfolio

Project 1 — Sales Analytics: Excel + SQL + Power BI → Revenue, Profit, Products, Regions, Customers, Trends

Project 2 — Customer Churn: SQL + Python + Power BI → Churn rate, Segments, Retention, Revenue at risk

Project 3 — Financial Analysis: Excel + Power BI → P&L, Budget vs Actual, Variance, Trends

Project 4 — E-commerce Analytics: SQL + Python + Power BI → Orders, Conversion, AOV, CLV

Project 5 — HR Analytics: Excel + SQL + Power BI → Headcount, Attrition, Salary, Tenure

🧠 STEP 17 — Explain Your Projects

Business Problem → Data → Cleaning → Transformation → Analysis → Visualization → Insights → Recommendations → Impact

💼 STEP 18 — Build Your Resume

🔎 STEP 19 — LinkedIn & GitHub

LinkedIn: Headline, About, Skills, Projects, Certifications, Posts on SQL, Power BI, Excel, Projects, Insights

GitHub: SQL projects, Python notebooks, Docs, Screenshots, Data dictionaries, README

🎤 STEP 20 — Interview Preparation

Excel: XLOOKUP, INDEX/MATCH, SUMIFS, COUNTIFS, PivotTables, Power Query

SQL: Joins, Aggregations, CTEs, Subqueries, Window functions, Ranking, Running totals

Power BI: DAX, CALCULATE, Data modeling, Relationships, Time intelligence

Python: Pandas, GroupBy, Merge, EDA

Business Cases: Sales drop, Churn increase, Revenue up but profit down, KPI anomaly

🗓️ Double Tap ❤️ For Detailed Explanation