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🆓 Resources to learn Power BI, Tableau & Data Visualisation Perfect channel to start learning everything about Data Analytics Admin: @coderfun

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Power BI & Tableau Resources

May 15, 2026, 10:02 AM

Important Topics You Should Know to Learn Python 👇

Lists, Strings, Tuples, Dictionaries, Sets – Learn the core data structures in Python.

Boolean, Arithmetic, and Comparison Operators – Understand how Python evaluates conditions.

Operations on Data Structures – Append, delete, insert, reverse, sort, and manipulate collections efficiently.

Reading and Extracting Data – Learn how to access, modify, and extract values from lists and dictionaries.

Conditions and Loops – Master if, elif, else, for, while, break, and continue statements.

Range and Enumerate – Efficiently loop through sequences with indexing.

Functions – Create functions with and without parameters, and understand *args and **kwargs.

Classes & Object-Oriented Programming – Work with init methods, global/local variables, and concepts like inheritance and encapsulation.

File Handling – Read, write, and manipulate files in Python.

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Power BI & Tableau Resources

May 15, 2026, 10:02 AM

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Power BI & Tableau Resources

May 15, 2026, 10:02 AM

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Power BI & Tableau Resources

May 15, 2026, 10:02 AM

📊 Essential Power BI Cheatsheet 📌📈

⬇️ Quick Power BI reference for beginners:

1) Power Query (Data Loading & Cleaning)
• Remove Columns, Filter Rows, Group By, Split Column
• Use “Transform Data” to shape your dataset
• M Language used in background (optional to edit manually)

2) DAX (Data Analysis Expressions)
• Create Calculated Columns & Measures
Total Sales = SUM(Sales[Amount])
Profit Margin = DIVIDE([Profit], [Revenue])

3) Visualizations
• Use Bar, Line, Pie, Card, Table, Matrix, Map
• Drag fields into Values, Axis, Legend, Filters
• Use Slicers for interactive filtering

4) Data Modeling
• Create relationships between tables
• Use 1-to-many links with a Star Schema
• Avoid circular relationships

5) Filters
• Report-Level, Page-Level, Visual-Level Filters
• Add Slicers for dynamic filtering

6) Bookmarks & Buttons
• Create interactive reports
• Add Back, Next, Reset Filters actions

7) Publishing & Sharing
• Publish to Power BI Service
• Share dashboards with others
• Schedule data refresh (Pro feature)

8) Power BI Service Features
• Create dashboards (pin visuals)
• Use Q&A (Ask a question using natural language)
• Monitor with Alerts and Goals

🛠 Pro Tip: Learn common DAX functions like CALCULATE, FILTER, ALL, RELATED to unlock advanced insights.

💬 Tap ❤️ for more Power BI tips!

947

Power BI & Tableau Resources

May 15, 2026, 10:02 AM

📷 Photo

Data Cleaning Tips ✅

1,040

Power BI & Tableau Resources

May 15, 2026, 10:02 AM

📷 Photo

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Power BI & Tableau Resources

May 15, 2026, 10:02 AM

Business Metrics Every Data Analyst Must Know ✅

Revenue Metrics
- Revenue: Total income from sales (e.g., monthly revenue ₹25 lakh)
- Gross Revenue vs Net Revenue: Gross (before costs), Net (after discounts and returns)
- Average Order Value: Revenue ÷ number of orders (e.g., ₹1,200 per order)

Growth Metrics
- Growth Rate: (Current − Previous) ÷ Previous (e.g., 15% month-over-month)
- Year-over-Year Growth: Compare same period last year

Customer Metrics
- Customer Count: Total active customers
- New vs Returning Customers: Shows retention strength
- Customer Acquisition Cost: Total marketing spend ÷ new customers
- Customer Lifetime Value: Total revenue from one customer over time

Retention and Churn
- Retention Rate: Customers who stayed ÷ total customers
- Churn Rate: Customers lost ÷ total customers (e.g., 1,000 customers, lost 50, churn rate 5%)

Marketing Metrics
- Conversion Rate: Conversions ÷ visitors
- Click-Through Rate: Clicks ÷ impressions
- Return on Ad Spend: Revenue ÷ ad spend

Product Metrics
- Daily Active Users: Users active per day
- Monthly Active Users: Users active per month
- DAU to MAU Ratio: Engagement strength

Operations Metrics
- Order Fulfillment Time: Time to deliver order
- Defect Rate: Defective units ÷ total units

Mini Task
Pick one business (E-commerce or EdTech). List 5 metrics it should track. Write one question each metric answers.

Let's take E-commerce:
1. Revenue: What's our total sales this month?
2. Customer Acquisition Cost: How much are we spending to acquire each new customer?
3. Retention Rate: How many customers are coming back to shop?
4. Average Order Value: What's the average amount customers are spending per order?
5. Order Fulfillment Time: How quickly are we delivering orders?

Double Tap ♥️ For More

Power BI & Tableau Resources

May 15, 2026, 10:02 AM

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Power BI & Tableau Resources

May 15, 2026, 10:02 AM

📷 Photo

Data Cleaning Tips ✅

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Power BI & Tableau Resources

Apr 5, 2026, 11:43 AM

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Power BI & Tableau Resources

Apr 5, 2026, 11:43 AM

Real-world Power BI Questions with Answers 🔥

Let’s use this small dataset to practice DAX & visuals in Power BI.

📊 Dataset: sales

1,050

Power BI & Tableau Resources

Apr 5, 2026, 11:43 AM

📷 Photo

1,020

Power BI & Tableau Resources

Apr 5, 2026, 11:43 AM

Power BI DAX Cheatsheet 🚀

1️⃣ Basics of DAX (Data Analysis Expressions)

DAX is used to create custom calculations in Power BI.

It works with tables and columns, not individual cells.

Functions in DAX are similar to Excel but optimized for relational data.

2️⃣ Aggregation Functions

SUM(ColumnName): Adds all values in a column.

AVERAGE(ColumnName): Finds the mean of values.

MIN(ColumnName): Returns the smallest value.

MAX(ColumnName): Returns the largest value.

COUNT(ColumnName): Counts non-empty values.

COUNTROWS(TableName): Counts rows in a table.

3️⃣ Logical Functions

IF(condition, result_if_true, result_if_false): Conditional statement.

SWITCH(expression, value1, result1, value2, result2, default): Alternative to nested IF.

AND(condition1, condition2): Returns TRUE if both conditions are met.

OR(condition1, condition2): Returns TRUE if either condition is met.

4️⃣ Time Intelligence Functions

TODAY(): Returns the current date.

YEAR(TODAY()): Extracts the year from a date.

TOTALYTD(SUM(Sales[Amount]), Date[Date]): Year-to-date total.

SAMEPERIODLASTYEAR(Date[Date]): Returns values from the same period last year.

DATEADD(Date[Date], -1, MONTH): Shifts dates by a specified interval.

5️⃣ Filtering Functions

FILTER(Table, Condition): Returns a filtered table.

ALL(TableName): Removes all filters from a table.

ALLEXCEPT(TableName, Column1, Column2): Removes all filters except specified columns.

KEEPFILTERS(FilterExpression): Keeps filters applied while using other functions.

6️⃣ Ranking & Row Context Functions

RANKX(Table, Expression, [Value], [Order]): Ranks values in a column.

TOPN(N, Table, OrderByExpression): Returns the top N rows based on an expression.

7️⃣ Iterators (Row-by-Row Calculations)

SUMX(Table, Expression): Iterates over a table and sums calculated values.

AVERAGEX(Table, Expression): Iterates over a table and finds the average.

MAXX(Table, Expression): Finds the maximum value based on an expression.

8️⃣ Relationships & Lookup Functions

RELATED(ColumnName): Fetches a related column from another table.

LOOKUPVALUE(ColumnName, SearchColumn, SearchValue): Returns a value from a column where another column matches a value.

9️⃣ Variables in DAX

VAR variableName = Expression RETURN variableName

Improves performance by reducing redundant calculations.

🔟 Advanced DAX Concepts

Calculated Columns: Created at the column level, stored in the data model.

Measures: Dynamic calculations based on user interactions in Power BI visuals.

Row Context vs. Filter Context: Understanding how DAX applies calculations at different levels.

Free Power BI Resources: https://whatsapp.com/channel/0029Vai1xKf1dAvuk6s1v22c

React with ❤️ for free cheatsheets

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Hope it helps :)

Power BI & Tableau Resources

Apr 5, 2026, 11:43 AM

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Power BI & Tableau Resources

Apr 5, 2026, 11:43 AM

Top 10 Power BI interview questions with answers:

1. What are the key components of Power BI?

Solution:

Power Query: Data transformation and preparation.

Power Pivot: Data modeling.

Power View: Data visualization.

Power BI Service: Cloud-based sharing and collaboration.

Power BI Mobile: Mobile reports and dashboards.

2. What is DAX in Power BI?

Solution:
DAX (Data Analysis Expressions) is a formula language used in Power BI to create calculated columns, measures, and tables.
Example:

TotalSales = SUM(Sales[Amount])

3. What is the difference between a calculated column and a measure?

Solution:

Calculated Column: Computed row by row in the data model.

Measure: Computed at the aggregate level based on filters in a visualization.

4. How do you connect Power BI to a database?

Solution:

1. Open Power BI Desktop.

2. Go to Home > Get Data > Database (e.g., SQL Server).

3. Enter server and database details, then load or transform data.

5. What is the role of relationships in Power BI?

Solution:
Relationships define how tables in a data model are connected. Power BI uses relationships to filter and calculate data across multiple tables.

6. What are slicers in Power BI?

Solution:
Slicers are visual filters that allow users to interactively filter data in reports.
Example: A slicer for "Region" lets users view data specific to a selected region.

7. How do you implement Row-Level Security (RLS) in Power BI?

Solution:

1. Define roles in Modeling > Manage Roles.

2. Use DAX expressions to restrict data (e.g., [Region] = "North").

3. Assign roles to users in the Power BI Service.

8. What are the different types of joins in Power BI?

Solution:
Power BI offers the following join types in Power Query:

Inner Join

Left Outer Join

Right Outer Join

Full Outer Join

Anti Join (Left/Right Exclusion)

9. What is the difference between Power BI Pro and Power BI Premium?

Solution:

Power BI Pro: Allows sharing and collaboration for individual users.

Power BI Premium: Provides dedicated resources, larger dataset sizes, and supports enterprise-level usage.

10. How can you optimize Power BI reports for performance?

Solution:

- Use summarized datasets.

- Reduce visuals on a single page.

- Optimize DAX expressions.

- Enable aggregations for large datasets.

- Use query folding in Power Query.

I have curated essential Power BI Interview Resources👇
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Like this post if you need more Power BI Resources 👍❤️

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Power BI & Tableau Resources

Apr 5, 2026, 11:43 AM

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Power BI & Tableau Resources

Apr 5, 2026, 11:43 AM

Power BI Cheat Sheet ✍

This Power BI cheatsheet is designed to be your quick reference guide for creating impactful reports and dashboards. Whether you’re a beginner exploring the basics or an experienced developer looking for a handy resource, this cheatsheet covers essential topics.

1. Connecting Data
- Import Data: *Home > Get Data > Select Data Source*
- Direct Query: *Home > Get Data > Select Data Source > Direct Query*

2. Data Transformation
- Power Query Editor: *Home > Transform Data*
- Remove Columns: *Transform > Remove Columns*
- Split Columns: *Transform > Split Column by Delimiter*
- Replace Values: *Transform > Replace Values*

3. Data Modeling
- Create Relationships: *Model > Manage Relationships > New*
- Edit Relationships: *Model > Manage Relationships > Edit*

4. DAX Calculations
- New Measure: *Modeling > New Measure*
- Common DAX Functions:
- SUM: SUM(table[column])
- AVERAGE: AVERAGE(table[column])
- IF: IF(condition, true_value, false_value)
- COUNTROWS: COUNTROWS(table)
- CALCULATE: CALCULATE(expression, filter)

5. Creating Visuals
- Select Visualization: *Visualizations Pane > Select Visual Type*
- Bar Chart: *Bar Chart Icon*
- Pie Chart: *Pie Chart Icon*
- Map Visual: *Map Icon*

6. Formatting Visuals
- Change Colors: *Format > Data Colors*
- Customize Titles: *Format > Title > Text*
- Adjust Axis: *Format > Y-Axis / X-Axis*

7. Filters
- Visual Level Filter: *Filter Pane > Add Filter for Selected Visual*
- Page Level Filter: *Filter Pane > Add Filter for Entire Page*
- Report Level Filter: *Filter Pane > Add Filter for Entire Report*

8. Slicers
- Add Slicer: *Visualizations > Slicer Icon*
- Customize Slicer: *Format > Edit Interactions*

9. Drillthrough
- Add Drillthrough: *Pages > Right Click on Field > Drillthrough*
- Back Button: *Insert > Button > Back Button*

10. Publishing & Sharing
- Publish Report: *Home > Publish > Select Workspace*
- Share Report: *File > Share > Publish to Web or Power BI Service*

11. Dashboards
- Create Dashboard: *Power BI Service > New Dashboard*
- Pin Visuals: *Pin Icon on Visual > Pin to Dashboard*

12. Export Options
- Export to PDF: *File > Export > PDF*
- Export Data: *Visual Options > Export Data*

Complete Checklist to become a Data Analyst: https://dataanalytics.beehiiv.com/p/data

You can refer these Power BI Interview Resources to learn more
👇👇
https://t.me/DataSimplifier

Like this post if you need more useful resources 👍♥️

Share with credits: https://t.me/sqlspecialist

Hope it helps :)

Power BI & Tableau Resources

Apr 5, 2026, 11:43 AM

📷 Photo

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Power BI & Tableau Resources

Apr 5, 2026, 11:43 AM

SQL is one of the core languages used in data science, powering everything from quick data retrieval to complex deep dive analysis. Whether you're a seasoned data scientist or just starting out, mastering SQL can boost your ability to analyze data, create robust pipelines, and deliver actionable insights.

Let’s dive into a comprehensive guide on SQL for Data Science!

I have broken it down into three key sections to help you:

𝟭. 𝗦𝗤𝗟 𝗖𝗼𝗻𝗰𝗲𝗽𝘁𝘀:
Get a handle on the essentials -> SELECT statements, filtering, aggregations, joins, window functions, and more.

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Now, let's move to the next topic in the Power BI Roadmap:

✅ Basic DAX Functions (SUM, COUNT, AVERAGE, DISTINCTCOUNT)

These are the most frequently used DAX functions and form the base of almost every dashboard.

1️⃣ Why to use DAX Functions

Almost every business question involves:
• Total values
• Counts
• Averages
• Unique counts

Examples:
• Total sales
• Number of customers
• Average order value
• Unique users

👉 These are solved using basic DAX functions.

2️⃣ SUM — Total Values
✅ SUM adds all numeric values in a column.

📌 Syntax:

Total Sales = SUM(Sales[SalesAmount])

💡 Use Case
• Total revenue
• Total quantity sold
• Total profit

3️⃣ COUNT — Count of Values
✅ COUNT counts the number of non-null numeric values in a column.

📌 Syntax
Total Orders = COUNT(Sales[OrderID])

💡 Important
• Works only with numeric columns
• Ignores null values

4️⃣ AVERAGE — Mean Value
✅ AVERAGE calculates the mean of numeric values.

📌 Syntax
Average Sales = AVERAGE(Sales[SalesAmount])

💡 Use Case
• Average order value
• Average salary
• Average revenue per day

5️⃣ DISTINCTCOUNT — Unique Count
✅ DISTINCTCOUNT counts unique values in a column.

📌 Syntax
Unique Customers = DISTINCTCOUNT(Sales[CustomerID])

💡 Use Case
• Unique users
• Unique customers
• Unique products sold

6️⃣ Real Business Example
Sales dataset:
• OrderID
• CustomerID
• SalesAmount

Measures:
• Total Sales = SUM(Sales[SalesAmount])
• Total Orders = COUNT(Sales[OrderID])
• Average Sales = AVERAGE(Sales[SalesAmount])
• Unique Customers = DISTINCTCOUNT(Sales[CustomerID])

7️⃣ Key Differences

• SUM: Total value
• COUNT: Number of records
• AVERAGE: Mean value
• DISTINCTCOUNT: Unique count

🔴 Common Beginner Mistakes
❌ Using COUNT on text columns
❌ Confusing COUNT vs DISTINCTCOUNT
❌ Using AVERAGE instead of weighted average
❌ Creating calculated columns instead of measures

🔑 Best Practice Rules
• Use measures for aggregation
• Use DISTINCTCOUNT for uniqueness
• Always check null values
• Validate results with sample data

Final Takeaway
These 4 functions cover 80% of basic analytics
They are building blocks for advanced DAX
Master them before moving ahead

✅ Double Tap ♥️ For More

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Mar 27, 2026, 04:39 AM

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∟📂 Dimensions vs Measures (Discrete/Continuous)
∟📂 Calculated Fields (Basic Math, String Functions)
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∟📂 Filters (Quick, Context, Top N)
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∟📂 Dashboards (Layout, Actions, Device Layouts)
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∟📂 Date Functions & Hierarchies
∟📂 Table Calculations (Running Total, Percent of Total)
∟📂 LOD Expressions (FIXED, INCLUDE, EXCLUDE)
∟📂 Parameters & Dynamic Dashboards
∟📂 Advanced Charts (Bullet, Heatmaps, Waterfall)
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✅ Power BI DAX Basics 📊🧠

DAX (Data Analysis Expressions) is Power BI's formula language for custom calculations, measures, and columns—essential for dynamic insights in 2025 reports.

1️⃣ SUM()
Adds column values.
Example: Total Sales = SUM(Sales[Amount])

2️⃣ AVERAGE()
Gets column average.
Example: Avg Salary = AVERAGE(Employee[Salary])

3️⃣ COUNT(), COUNTA(), COUNTROWS()
⦁ COUNT() for numerics
⦁ COUNTA() for non-blanks
⦁ COUNTROWS() for table rows
Examples: Total Orders = COUNT(Orders[OrderID]) | Total Customers = COUNTROWS(Customers)

4️⃣ CALCULATE()
Modifies calculation context (DAX's powerhouse).
Example: Sales East = CALCULATE(SUM(Sales[Amount]), Sales[Region] = "East")

5️⃣ FILTER()
Builds filtered tables for CALCULATE.
Example: High Sales = CALCULATE(SUM(Sales[Amount]), FILTER(Sales, Sales[Amount] > 1000))

6️⃣ IF()
Adds conditional logic.
Example: Sales Category = IF(Sales[Amount] > 500, "High", "Low")

7️⃣ SWITCH()
Handles multiple conditions cleanly.
Example: Rating = SWITCH(TRUE(), [Score] >= 90, "A", [Score] >= 75, "B", [Score] >= 60, "C", "Fail")

8️⃣ ALL()
Removes filters for totals.
Example: % of Total = DIVIDE(SUM(Sales[Amount]), CALCULATE(SUM(Sales[Amount]), ALL(Sales)))

9️⃣ DISTINCT()
Gets unique column values.
Example: Unique Products = DISTINCT(Sales[Product])

🔟 Measures vs Calculated Columns
⦁ Measures: Dynamic, context-based (best for visuals)
⦁ Calculated Columns: Row-by-row, stored (use sparingly for performance)

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Power BI DAX Cheatsheet 🚀

1️⃣ Basics of DAX (Data Analysis Expressions)

DAX is used to create custom calculations in Power BI.

It works with tables and columns, not individual cells.

Functions in DAX are similar to Excel but optimized for relational data.

2️⃣ Aggregation Functions

SUM(ColumnName): Adds all values in a column.

AVERAGE(ColumnName): Finds the mean of values.

MIN(ColumnName): Returns the smallest value.

MAX(ColumnName): Returns the largest value.

COUNT(ColumnName): Counts non-empty values.

COUNTROWS(TableName): Counts rows in a table.

3️⃣ Logical Functions

IF(condition, result_if_true, result_if_false): Conditional statement.

SWITCH(expression, value1, result1, value2, result2, default): Alternative to nested IF.

AND(condition1, condition2): Returns TRUE if both conditions are met.

OR(condition1, condition2): Returns TRUE if either condition is met.

4️⃣ Time Intelligence Functions

TODAY(): Returns the current date.

YEAR(TODAY()): Extracts the year from a date.

TOTALYTD(SUM(Sales[Amount]), Date[Date]): Year-to-date total.

SAMEPERIODLASTYEAR(Date[Date]): Returns values from the same period last year.

DATEADD(Date[Date], -1, MONTH): Shifts dates by a specified interval.

5️⃣ Filtering Functions

FILTER(Table, Condition): Returns a filtered table.

ALL(TableName): Removes all filters from a table.

ALLEXCEPT(TableName, Column1, Column2): Removes all filters except specified columns.

KEEPFILTERS(FilterExpression): Keeps filters applied while using other functions.

6️⃣ Ranking & Row Context Functions

RANKX(Table, Expression, [Value], [Order]): Ranks values in a column.

TOPN(N, Table, OrderByExpression): Returns the top N rows based on an expression.

7️⃣ Iterators (Row-by-Row Calculations)

SUMX(Table, Expression): Iterates over a table and sums calculated values.

AVERAGEX(Table, Expression): Iterates over a table and finds the average.

MAXX(Table, Expression): Finds the maximum value based on an expression.

8️⃣ Relationships & Lookup Functions

RELATED(ColumnName): Fetches a related column from another table.

LOOKUPVALUE(ColumnName, SearchColumn, SearchValue): Returns a value from a column where another column matches a value.

9️⃣ Variables in DAX

VAR variableName = Expression RETURN variableName

Improves performance by reducing redundant calculations.

🔟 Advanced DAX Concepts

Calculated Columns: Created at the column level, stored in the data model.

Measures: Dynamic calculations based on user interactions in Power BI visuals.

Row Context vs. Filter Context: Understanding how DAX applies calculations at different levels.

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Mar 27, 2026, 04:39 AM

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Quick Power BI Functions Cheat Sheet for Beginners 📊✍️

Aggregation Functions (DAX)
• SUM(column): Returns the total of a column.
• AVERAGE(column): Calculates the average value.
• COUNT(column): Counts non-blank rows in a column.
• DISTINCTCOUNT(column): Counts unique values.
• MAX(column): Returns the highest value.
• MIN(column): Returns the lowest value.

Filter Functions
• FILTER(table, condition): Returns a filtered table based on a condition.
• ALL(table/column): Removes filters from a table or column.
• ALLEXCEPT(table, column): Removes all filters except specified columns.
• VALUES(column): Returns unique values from a column.

Logical Functions
• IF(condition, true_result, false_result): Performs conditional logic.
• SWITCH(expression, value1, result1, …): Evaluates multiple conditions.
• AND(condition1, condition2): Returns TRUE if both conditions are true.
• OR(condition1, condition2): Returns TRUE if any condition is true.

Date Time Functions
• TODAY(): Returns the current date.
• NOW(): Returns the current date and time.
• YEAR(date): Extracts the year from a date.
• MONTH(date): Extracts the month from a date.
• DATEDIFF(date1, date2, interval): Returns the difference between two dates.

Text Functions
• CONCATENATE(text1, text2): Joins two text values.
• LEFT(text, num_chars): Extracts characters from the left.
• RIGHT(text, num_chars): Extracts characters from the right.
• LEN(text): Returns the length of text.
• FORMAT(value, text, format_string): Converts value to formatted text.

Relationship Functions
• RELATED(column): Fetches data from a related table.
• RELATEDTABLE(table): Returns related rows from another table.
• USERELATIONSHIP(column1, column2): Activates an inactive relationship.

Power BI Resources: https://whatsapp.com/channel/0029Vai1xKf1dAvuk6s1v22c

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