Post #2394

✅Core Data Analytics Concepts You Should Know: 1. Excel & Spreadsheets (Basics) - Data entry, sorting, filtering - Basic formulas: SUM, AVERAGE, IF, VLOOKUP, COUNTIF - Pivot tables & charts 2. Statistics & Math Basics - Mean, Median, Mode - Standard Deviation, Variance - Correlation & Regression - Probability basics 3. SQL (Data Extraction) - SELECT, WHERE, GROUP BY, HAVING - JOINs (INNER, LEFT, RIGHT) - Subqueries & CTEs - Window functions (ROW_NUMBER, RANK, etc.) 4. Data Cleaning & Wrangling - Handling missing values - Removing duplicates - Formatting and standardization 5. Data Visualization - Tools: Excel, Power BI, Tableau - Charts: Bar, Line, Pie, Histogram - Dashboards & storytelling with data 6. Programming with Python (Optional but recommended) - Pandas, NumPy for data manipulation - Matplotlib, Seaborn for visualization - Jupyter Notebooks for analysis 7. Business Understanding - Asking the right questions - KPI understanding - Domain knowledge 8. Projects & Case Studies - Sales analysis, Customer retention, Market trends - Use real-world datasets (Kaggle, Google Data Studio) 9. Reporting & Communication - Presenting insights clearly. - Visual storytelling - Report automation basics (Excel, PowerPoint) 10. Tools Knowledge - Power BI / Tableau - SQL Workbench / BigQuery - Excel / Google Sheets 👍 React ❤️ for more