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✅ Power BI Basics: Part-5 – Calculated Columns vs Measures 📊⚖️

📘 1️⃣ What is a Calculated Column?
A calculated column is created row by row in your table. It's stored like any other column and calculated when data is loaded.

Example:
Profit = Sales[Amount] - Sales[Cost]
Used when you need to group, sort, or filter using the new column.

✅ Best when:
• You need new data fields
• Used in visuals that need row context
• Required for slicers or categories

📘 2️⃣ What is a Measure?
A measure is calculated on the fly when used in a visual. It depends on the filters and context applied.

Example:
Total Profit = SUM(Sales[Profit])

✅ Best when:
• You want dynamic calculations
• Data should change with filters
• Ideal for KPIs, dashboards

📌 Key Differences:
• Columns = Static, stored per row
• Measures = Dynamic, context-sensitive
• Columns take more memory
• Measures are faster and more efficient

💡 Rule of Thumb:
Use calculated columns only if you must. Prefer measures for performance and flexibility.

🎯 Practice Task:
• Create a calculated column for Profit Margin
• Create a measure for Total Sales
• Use both in a bar chart and see the difference

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✅ Power BI Basics: Part-4 – DAX Functions 📊🧠

🔍 What is DAX?
DAX (Data Analysis Expressions) is the formula language used in Power BI to create custom calculations and measures.

You’ll use it to calculate totals, build KPIs, compare time periods, filter data, and much more.

📘 1. Basic DAX Functions
➤ SUM – Add values in a column
Total Sales = SUM(Sales[Amount])

➤ AVERAGE – Average of values
Average Discount = AVERAGE(Sales[Discount])

➤ COUNT / DISTINCTCOUNT
Order Count = COUNT(Sales[OrderID])
Unique Customers = DISTINCTCOUNT(Sales[CustomerID])

📘 2. Logical Functions
➤ IF Statement
Performance = IF(Sales[Amount] > 5000, "High", "Low")

➤ SWITCH – Simplify multiple conditions
Rating = SWITCH(Sales[Stars], 1, "Poor", 5, "Excellent", "Average")

📘 3. Time Intelligence Functions
➤ TOTALYTD
YTD Sales = TOTALYTD(SUM(Sales[Amount]), Dates[Date])

➤ SAMEPERIODLASTYEAR
Last Year Sales = CALCULATE(SUM(Sales[Amount]), SAMEPERIODLASTYEAR(Dates[Date]))

➤ DATEADD – Shift time
Previous Month Sales = CALCULATE(SUM(Sales[Amount]), DATEADD(Dates[Date], -1, MONTH))

📘 4. CALCULATE – The Most Powerful DAX Function
Changes the context in which a calculation is done.
High Value Sales = CALCULATE(SUM(Sales[Amount]), Sales[Amount] > 1000)

📌 Real-World Example:
You want to create a KPI card showing Total Sales, compare it with Last Year Sales, and show % Growth
Sales Growth % = DIVIDE([Total Sales] - [Last Year Sales], [Last Year Sales], 0)

💡 Pro Tip:
Use measures for calculations (not calculated columns) to improve performance and reusability.

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✅ Power BI Basics: Part-3 – Data Modeling 🧠🔗

Data modeling is the process of connecting multiple tables using relationships so Power BI can analyze data across them effectively.

📂 Types of Tables:
• Fact Table – Contains numeric data for analysis (e.g., Sales, Revenue)
• Dimension Table – Contains descriptive info (e.g., Product, Region, Date)

🔗 How to Create Relationships:
1️⃣ Go to Model View
2️⃣ Drag a field (e.g., Product ID) from one table to the matching field in another
3️⃣ Power BI will auto-detect and define the relationship type

🔁 Cardinality Options:
• One-to-Many (1:*): Common for dimensions to fact (e.g., one customer, many orders)
• Many-to-One (*:1): Reverse of above
• Many-to-Many (*:*): For advanced models, needs careful handling

🔁 Cross Filter Direction:
• Single – Only filters one way (default, safer)
• Both – Allows mutual filtering; useful for slicers

🛠️ Best Practices:
✔ Use surrogate keys (e.g., IDs) to build relationships
✔ Avoid circular relationships
✔ Normalize data where needed
✔ Create a Date Table for time-based analysis
✔ Keep the model clean avoid unnecessary joins

📌 Example:
Link your Sales table with:
– Products table (via ProductID)
– Customers table (via CustomerID)
– Calendar table (via Date)

💡 DAX helps you calculate values across tables once the model is set.

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✅ Power BI Basics: Part-2 – Data Transformation with Power Query 🧩🔄

🔍 What is Power Query? 
Power Query is Power BI’s built-in tool to connect, clean, and transform raw data before visualizing it.

📥 How to Import Data: 
1️⃣ Click “Home” > “Get Data” 
2️⃣ Choose source: Excel, CSV, SQL Server, Web, etc. 
3️⃣ Select the table or sheet → Click “Transform Data” to open Power Query Editor

🛠️ Power Query Editor – Key Sections: 
• Queries Pane – Lists all loaded tables/queries 
• Data Preview – Shows the current table data 
• Applied Steps – Every change you make is recorded here 
• Ribbon Tools – Options to clean, shape, and merge data

🧹 Common Data Transformations: 
✔ Remove columns/rows 
✔ Rename columns 
✔ Change data types (text, number, date) 
✔ Filter rows 
✔ Split columns (by delimiter) 
✔ Merge queries (joins) 
✔ Append queries (stack tables) 
✔ Create calculated columns 

⚙️ Applied Steps: 
Each step is tracked, so you can go back or edit them anytime without touching the original source file.

📌 Example: 
Import an Excel file → remove blank rows → change “Date” to proper format → split “Full Name” → load clean data to Power BI

💡 Pro Tip: Use “Close  Apply” to save your cleaned data and move to Report View.

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✅ Power BI Basics: Part-1 📊💡

🔍 What is Power BI?
Power BI is a Microsoft business analytics tool used to visualize data, build reports, and share insights across teams.

📌 Key Features:
• Interactive dashboards
• Real-time data updates
• Easy drag-and-drop interface
• Integration with Excel, SQL, Azure, and more

🧭 Power BI Interface Overview:

1️⃣ Home Tab
• Quick access to importing data, creating visuals, and formatting reports

2️⃣ Report View
• Main canvas to design dashboards using charts, tables, maps, etc.

3️⃣ Data View
• See and inspect your datasets (rows & columns like Excel)

4️⃣ Model View
• Create relationships between tables (like foreign key joins)

5️⃣ Fields Pane
• Lists all tables, columns, and measures you’ve imported

6️⃣ Visualizations Pane
• Choose chart types (bar, pie, line, map, KPI, etc.)
• Customize titles, legends, filters, colors

7️⃣ Filters Pane
• Apply visual, page, or report-level filters for data control

🧰 Basic Power BI Workflow:
1. Get Data – Import from Excel, SQL, CSV, etc.
2. Transform Data – Use Power Query to clean data
3. Model Data – Define relationships & calculated fields
4. Visualize – Drag fields onto canvas and build visuals
5. Publish – Share reports on Power BI Service

💡 Pro Tip: Use slicers to let users filter data interactively!

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🚀 Roadmap to Master Power BI in 30 Days! 📊💡

📅 Week 1: Basics Interface
🔹 Day 1–2: What is Power BI? Setup Interface Tour
🔹 Day 3–4: Data import (Excel, CSV, SQL)
🔹 Day 5–7: Data transformation using Power Query (cleaning, filtering)

📅 Week 2: Data Modeling DAX
🔹 Day 8–9: Relationships between tables
🔹 Day 10–11: Basic DAX (SUM, COUNT, CALCULATE)
🔹 Day 12–14: Calculated columns measures

📅 Week 3: Visualizations Dashboards
🔹 Day 15–17: Bar, line, pie, table, card visuals
🔹 Day 18–19: Slicers, filters, drill-throughs
🔹 Day 20–21: Design interactive dashboards

📅 Week 4: Advanced Deployment
🔹 Day 22–24: Time intelligence (YTD, MTD, comparisons)
🔹 Day 25–26: Publish to Power BI Service + schedule refresh
🔹 Day 27–28: Row-Level Security
🔹 Day 29–30: Build a real-world dashboard project

💬 Tap ❤️ for more!

✅ Power BI Interview Questions – Part 2 ⚡📊

1️⃣ What is a relationship in Power BI?
It links tables using keys (like foreign key in SQL) so data can interact across tables.

2️⃣ Types of relationships in Power BI?
• One-to-one
• One-to-many (most common)
• Many-to-many

3️⃣ What is the difference between star schema and snowflake schema?
• Star Schema: Simple, with denormalized tables
• Snowflake Schema: Complex, with normalized sub-tables

4️⃣ What is row-level security (RLS)?
A feature that restricts data access for users based on filters you define.

5️⃣ What are bookmarks in Power BI?
Used to capture the current state of a report page and navigate between views or filters.

6️⃣ What is drill-through in Power BI?
Allows users to right-click and explore detailed data related to a particular field.

7️⃣ What is the use of tooltips?
Hover-based popups that show extra information about visuals or data points.

8️⃣ Difference between ALL and ALLEXCEPT in DAX?
• ALL: Removes all filters
• ALLEXCEPT: Keeps specific filters intact while removing others

9️⃣ How do you optimize Power BI reports?
• Reduce visuals on a page
• Use measures instead of calculated columns
• Limit imported data
• Optimize DAX queries

🔟 What visuals are commonly used?
• Bar/Column Chart
• Pie/Donut Chart
• Table/Matrix
• Card
• Map
• Slicer

💬 Tap ❤️ for Part 3