Data Analysis Books - ресурсы

✅ Power BI Basics 📊🚀 👉 Power BI is one of the most popular Business Intelligence BI tools used for: ✔ Data visualization ✔ Dashboard creation ✔ Business reporting It is widely used by: ✔ Data Analysts ✔ Business Analysts ✔ Data Scientists 🔹 1. What is Power BI? Power BI is a Microsoft tool used to transform raw data into: 📊 Interactive dashboards 📈 Reports 📉 Visual insights 🔥 2. Components of Power BI ✅ Power BI Desktop 👉 Used to create reports & dashboards. ✅ Power BI Service 👉 Cloud platform for sharing reports online. ✅ Power BI Mobile 👉 Access dashboards on mobile devices. 🔹 3. Power BI Workflow ⭐ Data → Cleaning → Modeling → Visualization → Dashboard → Sharing 🔹 4. Connecting Data Sources Power BI can connect with: ✔ Excel ✔ SQL Database ✔ CSV Files ✔ APIs ✔ Cloud services 🔹 5. Power Query Data Cleaning Used for: ✔ Removing duplicates ✔ Changing data types ✔ Filtering rows ✔ Merging data 👉 Similar to data cleaning in Pandas. 🔹 6. Data Modeling 👉 Relationships between tables. Examples: ✔ One-to-Many ✔ Many-to-One 🔥 7. Visualizations in Power BI Popular visuals: ✔ Bar Chart ✔ Line Chart ✔ Pie Chart ✔ Table ✔ KPI Cards ✔ Maps 🔹 8. DAX Data Analysis Expressions DAX is the formula language of Power BI. Example: Total Sales = SUM(Sales[Amount]) 🔹 9. Why Power BI is Important? ✔ Highly demanded skill ✔ Used in real companies ✔ Important for dashboards & reporting ✔ Great for storytelling with data 🎯 Today’s Goal ✔ Understand Power BI basics ✔ Learn workflow ✔ Understand Power Query & DAX ✔ Learn dashboard concepts Power BI Resources: Ссылка скрыта 💬 Tap ❤️ for more!

Excel Basics for Data Analytics Excel sits at the start of most analysis work. What you use Excel for • Cleaning raw data • Exploring patterns • Quick summaries for teams Core concepts you must know • Data setup – Freeze header row. View → Freeze Top Row. – Convert range to table. Ctrl + T. – Use proper headers. No merged cells. One value per cell. • Data cleaning – Remove duplicates. Data → Remove Duplicates. – Trim extra spaces. =TRIM(A2) – Convert text to numbers. =VALUE(A2) – Fix date format. Format Cells → Date. – Handle blanks. Filter blanks, fill or delete. – Find and replace. Ctrl + H. • Essential formulas – Math and counts ▪ SUM. =SUM(A2:A100) ▪ AVERAGE. =AVERAGE(A2:A100) ▪ MIN. =MIN(A2:A100) ▪ MAX. =MAX(A2:A100) ▪ COUNT. Counts numbers. ▪ COUNTA. Counts non blanks. ▪ COUNTBLANK. Counts blanks. – Conditional formulas ▪ IF. =IF(A2>5000,"High","Low") ▪ IFS. Multiple conditions. ▪ AND. =AND(A2>5000,B2="West") ▪ OR. =OR(A2>5000,A2 10000 in green. • Pivot tables – Insert → PivotTable. – Rows. Category or Product. – Values. Sum, Count, Average. – Filters. Date, Region. – Refresh after data update. • Charts you must know – Column. Comparison. – Bar. Ranking. – Line. Trends over time. – Pie. Share or percentage. – Combo. Actual vs target. • Data validation – Dropdown list. Data → Data Validation → List. – Prevent wrong entries. • Useful shortcuts – Ctrl + Arrow. Jump data. – Ctrl + Shift + Arrow. Select range. – Ctrl + 1. Format cells. – Ctrl + L. Apply filter. – Alt + =. Auto sum. – Ctrl + Z / Y. Undo redo. • Common analyst mistakes to avoid – Merged cells. – Hard coded totals. – Mixed data types in one column. – No backup before cleaning. • Daily practice task – Download any sales CSV. – Clean it. – Build one pivot table. – Create one chart. Excel Resources: Ссылка скрыта Data Analytics Roadmap: Ссылка скрыта Double Tap ♥️ For More