Post #2330

✅Data Analyst Learning Checklist🧠 📚Foundations - [ ] Excel / Google Sheets - [ ] Basic Statistics & Probability - [ ] Python (or R) for Data Analysis - [ ] SQL for Data Querying 📊Data Handling & Manipulation - [ ] NumPy & Pandas - [ ] Data Cleaning & Wrangling - [ ] Handling Missing Data & Outliers - [ ] Merging, Grouping & Aggregating Data 📈Data Visualization - [ ] Matplotlib & Seaborn (Python) - [ ] Power BI / Tableau - [ ] Creating Dashboards - [ ] Storytelling with Data 🧠Analytical Thinking - [ ] Exploratory Data Analysis (EDA) - [ ] Trend & Pattern Detection - [ ] Correlation & Causation - [ ] A/B Testing & Hypothesis Testing 🛠️Tools & Platforms - [ ] Jupyter Notebook / Google Colab - [ ] SQL IDEs (e.g., MySQL Workbench) - [ ] Git & GitHub - [ ] Google Data Studio / Looker 📂Projects to Build - [ ] Sales Data Dashboard - [ ] Customer Segmentation - [ ] Marketing Campaign Analysis - [ ] Product Usage Trend Report - [ ] HR Attrition Analysis 🚀Practice & Growth - [ ] Kaggle Notebooks & Datasets - [ ] DataCamp / LeetCode (SQL) - [ ] Real-world Data Challenges - [ ] Create a Portfolio on GitHub Tap ❤️ for more!