Ways to improve the performance of Tableau

👉🏻 Use an Extract to make workbooks run faster.
👉🏻 Reduce the number of marks on the view to avoid information overload.
👉🏻 Hide unused fields.
👉🏻 Use Context filters.
👉🏻 Use indexing in tables and use the same fields for filtering.
👉🏻 Remove unnecessary calculations and sheets.

If your data can be visualized as a bar chart, column chart, or line graph...

...use a bar chart, column chart, or line graph.

Fancy doesn't always mean better and, in fact, it often means worse.

Your job as a data analyst is to make the data and insights accessible to stakeholders, which means using visuals that a non-technical person can understand.

Are there charts and graphs that are more fun to look at?

Sure. Sankey diagrams, word clouds, waterfall charts, and radar charts have their place.

But I would say that 80+% of data visualizations can be done using a very small handful of clear, simple charts.

Your stakeholders will thank you.

And your future self will thank you when you don't have to help interpret the data viz every time someone looks at it.

Win-win.

Are you gearing up for a Power BI interview? 🤔

Can you explain a few visualizations you have used in your projects and why you chose those charts?"
Be sure to name the charts and explain why they fit specific scenarios.

Bar Chart:
Example: Comparing the number of apples, bananas, and oranges sold at a fruit stand. Reason: Bar charts are good for comparing the amounts of different items side by side.

Column Chart:
Example: Showing how many hours a student studied each day for a week. Reason: Column charts help you see how values change over specific periods, like days or months.

Line Chart:
Example: Tracking the temperature at noon each day for a month. Reason: Line charts are perfect for showing trends over time, like how the temperature goes up and down.

I have curated the best interview resources to crack Power BI Interviews 👇👇
https://topmate.io/analyst/866125
 
Like this post if you need more resources like this 👍❤️

Interview Question:

1. Which type of chart will you use to compare and show the sales by region in Power BI?

Answer:

To compare and show the sales by region in Power BI, a bar chart or column chart is typically used. These charts are effective for comparing data across different categories, such as regions, and they clearly display differences in sales values.

Sample Dataset:

| Region | Quarter | Product | Sales |
|---------|---------|----------|-------|
| North | Q1 | Product A| 50000 |
| North | Q1 | Product B| 30000 |
| North | Q2 | Product A| 40000 |
| North | Q2 | Product B| 35000 |
| South | Q1 | Product A| 45000 |
| South | Q1 | Product B| 25000 |
| South | Q2 | Product A| 30000 |
| South | Q2 | Product B| 32000 |
| East | Q1 | Product A| 42000 |
| East | Q1 | Product B| 28000 |
| East | Q2 | Product A| 39000 |
| East | Q2 | Product B| 31000 |
| West | Q1 | Product A| 41000 |
| West | Q1 | Product B| 29000 |
| West | Q2 | Product A| 35000 |
| West | Q2 | Product B| 29000 |
| Central | Q1 | Product A| 48000 |
| Central | Q1 | Product B| 32000 |
| Central | Q2 | Product A| 43000 |
| Central | Q2 | Product B| 31000 |

Steps to Visualize in Power BI:

1. Import the Dataset:
- Open Power BI Desktop.
- Import the dataset into Power BI.

2. Create the Bar Chart:
- In the Fields pane, select the fields Region, Quarter, Product, and Sales.
- From the Visualizations pane, select the Clustered Bar Chart or Stacked Bar Chart icon.

3. Configure the Chart:
- Drag Region to the Axis field well.
- Drag Sales to the Values field well.
- Drag Quarter and Product to the Legend or Small Multiples field well to add additional dimensions.

4. Customize the Chart:
- Add data labels to show the exact sales figures.
- Adjust colors and styles to improve readability.
- Use filters or slicers to focus on specific regions, quarters, or products if needed.

Answer Explanation:
A bar chart or column chart with additional dimensions like Quarter and Product allows for a more detailed comparison of sales by region. You can see not only the total sales per region but also how each product performs across different quarters within each region.

### Additional Interview Questions:

2. How can you create a calculated column in Power BI to show the profit margin percentage?

Answer:

To create a calculated column in Power BI to show the profit margin percentage, follow these steps:

1. Go to the Data view in Power BI Desktop.
2. Select the table where you want to create the new column.
3. Click on the New Column button in the Modeling tab.
4. Enter the formula for the calculated column. For example:
Profit Margin = (Sales - Cost) / Sales * 100
5. Press Enter.

This will create a new column in your table showing the profit margin percentage for each row.

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

Answer:

The key difference between a measure and a calculated column in Power BI is how and when they are calculated and used:

- A calculated column is calculated row by row when the data is loaded into the data model. It is stored in the table and can be used like any other column in the table.
- A measure, on the other hand, is calculated on the fly based on the context of the visualization. Measures are typically used for aggregations, such as sums, averages, or counts, and they are not stored in the table but are recalculated as needed.

4. How would you handle a situation where your Power BI report is performing slowly?

Answer:

To handle a situation where a Power BI report is performing slowly, you can:

1. Optimize your data model by removing unnecessary columns and tables.

2. Use relationships and filtering carefully to minimize the amount of data processed.
3. Avoid using complex DAX calculations in visuals; instead, create calculated columns or tables if needed.
4. Use aggregate tables or pre-aggregated data to reduce the volume of data processed in visuals.
5. Ensure that your data source is optimized for performance, such as indexing important columns or partitioning large tables.
6. Use Power BI Performance Analyzer to identify and troubleshoot performance bottlenecks in your report.

𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 𝐑𝐞𝐚𝐥 𝐓𝐢𝐦𝐞 𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐒𝐞𝐫𝐢𝐞𝐬 📊

𝐃𝐢𝐟𝐟𝐞𝐫𝐞𝐧𝐜𝐞 𝐛𝐞𝐭𝐰𝐞𝐞𝐧 𝐑𝐞𝐩𝐨𝐫𝐭𝐬 𝐯𝐬 𝐃𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝𝐬

𝐑𝐞𝐩𝐨𝐫𝐭:
𝐖𝐡𝐞𝐫𝐞 𝐲𝐨𝐮 𝐦𝐚𝐤𝐞 𝐢𝐭: Power BI Desktop,
𝐖𝐡𝐚𝐭 𝐢𝐭 𝐬𝐡𝐨𝐰𝐬: Reports in Power BI are detailed documents that use charts, graphs, and tables to explain your data. They help you analyze trends and find insights.

𝐃𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝:
𝐖𝐡𝐞𝐫𝐞 𝐲𝐨𝐮 𝐦𝐚𝐤𝐞 𝐢𝐭: Power BI service
𝐖𝐡𝐚𝐭 𝐢𝐭 𝐬𝐡𝐨𝐰𝐬: Dashboards is a display of key metrics and KPIs from multiple reports. They give you a quick overview of your data.

𝐘𝐨𝐮 𝐜𝐚𝐧 𝐬𝐞𝐥𝐞𝐜𝐭 𝐯𝐢𝐬𝐮𝐚𝐥𝐬 𝐟𝐫𝐨𝐦 𝐦𝐮𝐥𝐭𝐢𝐩𝐥𝐞 𝐫𝐞𝐩𝐨𝐫𝐭𝐬 𝐭𝐨 𝐜𝐫𝐞𝐚𝐭𝐞 𝐚 𝐬𝐢𝐧𝐠𝐥𝐞 𝐝𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝.

Here's the list of advanced DAX functions which we use mostly in our projects to get the insights easily for our client:

1. ALLSELECTED
2. USERELATIONSHIP
3. CROSSFILTER
4. TREATAS
6. CONTAINS
7. SUMMARIZE
8. ADDCOLUMNS
9. GENERATE
10. TOPN
11. RANK.EQ
12. EARLIER
13. INTERSECT
14.EXCEPT
15. UNION
16. LOOKUPVALUE
17. ISINSCOPE
18. SELECTEDVALUE
19. VAR
20. SUMMARIZECOLUMNS
21. NATURALINNERJOIN

Go through all these DAX functions, their formulas and their use thoroughly to understand the functionality.

I have curated the best interview resources to crack Power BI Interviews 👇👇
https://topmate.io/analyst/866125

Hope you'll like it

Like this post if you need more content like this 👍❤️

📊 𝐒𝐭𝐞𝐩-𝐛𝐲-𝐒𝐭𝐞𝐩 𝐆𝐮𝐢𝐝𝐞 𝐭𝐨 𝐥𝐞𝐚𝐫𝐧 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈-

1. What is Power BI Desktop, Power BI Service & Power BI Report Server?

2. Connecting to different data sources: Excel, SQL Server, web, etc.

3. Common Charts: bar charts, column charts, line charts, pie charts, slicers

4. Side Panes: Fields, Visualizations, Formatting and Filters

5. Power Query Editor- filtering, sorting, merging, appending, pivoting, unpivoting, splitting columns, add columns, conditional columns

6. Relationships between tables- one-to-many, many-to-one, and many-to-many

7. DAX- calculated columns & measures

8. Using bookmarks and buttons for navigation

9. Drill-through options in charts

10. RLS to restrict data access

11. Publishing reports from Power BI Desktop to the Power BI Service

I have curated the best interview resources to crack Power BI Interviews 👇👇
https://topmate.io/analyst/866125

Hope you'll like it

Like this post if you need more content like this 👍❤️

𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 𝐫𝐞𝐩𝐨𝐫𝐭 𝐢𝐬 𝐫𝐮𝐧𝐧𝐢𝐧𝐠 𝐬𝐥𝐨𝐰𝐥𝐲. 𝐖𝐡𝐚𝐭 𝐬𝐭𝐞𝐩𝐬 𝐰𝐨𝐮𝐥𝐝 𝐲𝐨𝐮 𝐭𝐚𝐤𝐞 𝐭𝐨 𝐝𝐢𝐚𝐠𝐧𝐨𝐬𝐞 𝐚𝐧𝐝 𝐟𝐢𝐱 𝐭𝐡𝐞 𝐩𝐫𝐨𝐛𝐥𝐞𝐦?

👉 Check Data Volume: Large datasets can slow down your report. Try to reduce the amount of data by filtering or aggregating it.

👉 Optimize Data Model: Remove any unnecessary columns or tables. Use appropriate data types and relationships.

👉 Review DAX Calculations: Simplify complex DAX formulas. Avoid using too many calculated columns or measures.

👉 Manage Visualizations: Limit the number of visuals on a single report page. Use simpler visuals when possible.

👉 Reduce Query Load: Use "Query Folding" to push operations back to the data source. Make sure your queries are efficient and optimized.

👉 Enable Performance Analyzer: In Power BI Desktop, go to "View" > "Performance Analyzer." Run it to see which visuals or queries are taking the most time.

👉 Optimize Data Refresh: Schedule refreshes during off-peak hours. Ensure incremental refresh is set up if possible.

👉 Improve Power BI Service Settings: Ensure your Power BI workspace is in the correct region. Check for any limitations or restrictions on the service.

I have curated the best interview resources to crack Power BI Interviews 👇👇
https://topmate.io/analyst/866125

Hope you'll like it

Like this post if you need more content like this 👍❤️

IBM Power BI Interview Questions

1. How can you create and configure a data gateway in Power BI?
2. Explain the process of creating a dynamic tooltip in Power BI.
3. How does Power BI handle real-time data streaming, and what are its use cases?
4. What are the different types of data relationships in Power BI?
5. Describe the purpose and usage of Power BI Premium.
6. How do you create a sunburst chart in Power BI?
7. What are the differences between a line chart and an area chart in Power BI?
8. Explain the concept of Data Analysis Expressions (DAX) in Power BI.
9. What is the significance of the "Drillthrough" feature in Power BI?

## Capgemini Power BI Interview Questions

1. How do you implement row-level security (RLS) in Power BI?
2. What are the best practices for designing a Power BI dashboard?
3. Can you explain the Power BI report lifecycle?
4. How does Power BI handle data refresh and scheduling?
5. What is the role of the Query Editor in Power BI?
6. How do you create a funnel chart in Power BI?
7. What is the difference between a measure and a KPI in Power BI?
8. Explain the concept of hierarchical slicers in Power BI.
9. How do you use bookmarks in Power BI to enhance report interactivity?

## Deloitte Power BI Interview Questions

1. How can you configure and use custom visuals in Power BI?
2. What techniques can be employed to improve query performance in Power BI?
3. Describe the integration capabilities of Power BI with other Microsoft services.
4. What is the difference between Import mode and DirectQuery mode in Power BI?
5. How do you create a pareto chart in Power BI?
6. What are the advantages of using Power BI templates?
7. Explain the concept of dataflows in Power BI.
8. What is the purpose of the "Merge Queries" feature in Power BI, and how is it used?
9. How do you create and manage data alerts in Power BI?

I have curated the best interview resources to crack Power BI Interviews 👇👇
https://topmate.io/analyst/866125

Hope you'll like it

Like this post if you need more content like this 👍❤️

Some complex scenario-based Tableau interview questions asked in top MNCs:

1. Complex Data Blending with Different Granularity Levels:
- Scenario: You are given three data sources: daily sales data, monthly budget data, and quarterly market analysis data. The goal is to create a unified dashboard that compares actual sales to budget and market trends. Discuss the challenges you might face due to the different granularity levels of the data and describe how you would use Tableau to blend these data sources effectively while maintaining accurate comparisons.
- Key Focus: Data Blending, Granularity, LOD Expressions, Aggregations.

2. Dynamic Hierarchical Filtering and Drill-Down Analysis:
- Scenario: Create a dashboard for a telecom company that allows users to drill down from country to region to city level to analyze network performance metrics such as call drop rates, average data speeds, and customer complaints. The dashboard should provide dynamic hierarchical filters that update based on the level of detail the user selects. Describe your approach to setting up these filters and ensuring the drill-down functionality works seamlessly.
- Key Focus: Hierarchical Filters, Drill-Down Analysis, Context Filters, Dashboard Interactivity.

3. Advanced Time Series Analysis with Forecasting:
- Scenario: You need to create a time series analysis dashboard for an e-commerce company to forecast future sales based on historical data. The dashboard should include monthly, quarterly, and yearly sales trends, seasonal patterns, and predictive forecasts. Explain how you would handle seasonality, outliers, and trend analysis in Tableau, and how you would implement advanced forecasting techniques to provide accurate predictions.
- Key Focus: Time Series Analysis, Forecasting, Seasonality, Outlier Detection, Trend Lines.

I have curated the best interview resources to crack Power BI Interviews 👇👇
https://topmate.io/analyst/866125

Hope you'll like it

Like this post if you need more content like this 👍❤️

Power BI Learning Plan in 2024
👇👇
https://t.iss.one/sqlspecialist/745

10 𝐓𝐢𝐩𝐬 𝐭𝐨 𝐈𝐧𝐜𝐫𝐞𝐚𝐬𝐞 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 𝐑𝐞𝐩𝐨𝐫𝐭 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐜𝐲 𝐚𝐧𝐝 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐚𝐭𝐢𝐨𝐧. 𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 𝐩𝐨𝐰𝐞𝐫 𝐁𝐢 𝐐𝐮𝐞𝐬𝐭𝐢𝐨𝐧.
.
As a Senior Data Analyst, I have learned some valuable tips to enhance report efficiency and optimization.

1. 𝐋𝐢𝐦𝐢𝐭 𝐃𝐚𝐭𝐚 𝐋𝐨𝐚𝐝: Load only the data you need. Use filters and remove unnecessary columns to minimize data volume.

2. 𝐄𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭 𝐃𝐚𝐭𝐚 𝐌𝐨𝐝𝐞𝐥: opt for a star schema design. It simplifies relationships and improves performance.

3. 𝐑𝐞𝐝𝐮𝐜𝐞 𝐕𝐢𝐬𝐮𝐚𝐥𝐬: Avoid overcrowding your reports with too many visuals. Each visual query impacts performance.

4. 𝐔𝐭𝐢𝐥𝐢𝐳𝐞 𝐀𝐠𝐠𝐫𝐞𝐠𝐚𝐭𝐢𝐨𝐧𝐬: Use aggregations to pre-calculate and store summaries of data, reducing the processing load.

5. 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐞 𝐃𝐀𝐗 𝐐𝐮𝐞𝐫𝐢𝐞𝐬: Write efficient DAX formulas. Use variables to store intermediate results and avoid repeated calculations.

6. 𝐃𝐢𝐬𝐚𝐛𝐥𝐞 𝐀𝐮𝐭𝐨 𝐃𝐚𝐭𝐞/𝐓𝐢𝐦𝐞: Turn off auto date/time for new files in Power BI options. It can reduce the model size significantly.

7. 𝐈𝐧𝐜𝐫𝐞𝐦𝐞𝐧𝐭𝐚𝐥 𝐑𝐞𝐟𝐫𝐞𝐬𝐡: Implement incremental refresh for large datasets. It updates only the new or changed data.

8. 𝐎𝐩𝐭𝐢𝐦𝐢𝐳𝐞 𝐐𝐮𝐞𝐫𝐲 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞: Use query folding whenever possible. Push transformations to the source database.

9. 𝐔𝐬𝐞 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 𝐒𝐞𝐫𝐯𝐢𝐜𝐞 𝐅𝐞𝐚𝐭𝐮𝐫𝐞𝐬: Leverage features like dataflows and shared datasets to optimize data management and reusability.

10. 𝐌𝐨𝐧𝐢𝐭𝐨𝐫 𝐚𝐧𝐝 𝐀𝐧𝐚𝐥𝐲𝐳𝐞 𝐏𝐞𝐫𝐟𝐨𝐫𝐦𝐚𝐧𝐜𝐞: Use Performance Analyzer in Power BI Desktop to identify and resolve performance bottlenecks.

📌 Implementing these tips can significantly enhance your Power BI reports' efficiency and responsiveness.

I have curated the best interview resources to crack Power BI Interviews 👇👇
https://topmate.io/analyst/866125

Hope you'll like it

Like this post if you need more content like this 👍❤️

Power BI One Month Roadmap

Week 1: Basic Concepts

1. Power BI Beginner Tutorial by Guy in a Cube
2. Microsoft Documentation: Getting Started with Power BI Desktop
3. Power BI Data Transformation by Simplilearn
4. Data Modeling in Power BI by Curbal

Week 2: Data Visualization

5. Visualizing Data in Power BI by edureka!
6. Using Maps in Power BI by Guy in a Cube

7. Creating Interactive Reports by Guy in a Cube
8. Microsoft Documentation: Add Drillthrough to Your Reports

Week 3: DAX (Data Analysis Expressions)

9. Introduction to DAX by Curbal
10. Microsoft Documentation: DAX Basics in Power BI Desktop

11. DAX Basics Tutorial by Microsoft Power BI
12. Power BI DAX Tutorial by Edureka

Week 4: Publishing and Sharing

13. Publishing Reports in Power BI by Curbal
14. Sharing Power BI Dashboards by Pragmatic Works
15. Power BI Mobile Overview by Guy in a Cube

I have curated the best interview resources to crack Power BI Interviews 👇👇
https://topmate.io/analyst/866125

Hope you'll like it

Like this post if you need more content like this 👍❤️

𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 𝐑𝐞𝐚𝐥 𝐓𝐢𝐦𝐞 𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐒𝐞𝐫𝐢𝐞𝐬 📊

𝐃𝐨 𝐲𝐨𝐮 𝐤𝐧𝐨𝐰 𝐚𝐛𝐨𝐮𝐭 𝐭𝐡𝐞 𝐑𝐎𝐖 𝐃𝐀𝐗 𝐟𝐮𝐧𝐜𝐭𝐢𝐨𝐧 𝐢𝐧 𝐏𝐨𝐰𝐞𝐫 𝐁𝐈?

The 𝐑𝐎𝐖 𝐟𝐮𝐧𝐜𝐭𝐢𝐨𝐧 in DAX is a handy way to create a mini-table with just one row and some columns. This can be super useful for quick calculations or displaying small sets of data dynamically within your Power BI reports.

1. Click on 'New Table'.
2. Now, enter this formula:
ProductInfo =
ROW(
"Product Name", "Widget",
"Price", 25,
"Quantity", 100
)

- 𝐏𝐫𝐨𝐝𝐮𝐜𝐭𝐈𝐧𝐟𝐨 is the name of your new mini table.
- "𝐏𝐫𝐨𝐝𝐮𝐜𝐭 𝐍𝐚𝐦𝐞", "𝐏𝐫𝐢𝐜𝐞", "𝐐𝐮𝐚𝐧𝐭𝐢𝐭𝐲" are the column names of your new mini table.
- "𝐖𝐢𝐝𝐠𝐞𝐭", 𝟐𝟓, 𝟏𝟎𝟎 are the values for each column

𝐖𝐡𝐚𝐭 𝐢𝐟 𝐲𝐨𝐮 𝐰𝐚𝐧𝐭 𝐦𝐨𝐫𝐞 𝐫𝐨𝐰𝐬? 🤔
To create a table with multiple rows, you can use the𝐔𝐍𝐈𝐎𝐍 function to combine multiple ROW functions.

Here’s an example with three products:

Products =
UNION(
ROW("Product Name", "Widget", "Price", 25, "Quantity", 100),
ROW("Product Name", "Gadget", "Price", 30, "Quantity", 150),
ROW("Product Name", "Thingamajig", "Price", 45, "Quantity", 200)
)

I have curated the best interview resources to crack Power BI Interviews 👇👇
https://topmate.io/analyst/866125

Hope you'll like it

Like this post if you need more content like this 👍❤️

𝐏𝐨𝐰𝐞𝐫 𝐁𝐈 𝐑𝐞𝐚𝐥 𝐓𝐢𝐦𝐞 𝐏𝐫𝐨𝐣𝐞𝐜𝐭 𝐒𝐞𝐫𝐢𝐞𝐬 📊

I recently worked on a project for a client dealing with a large dataset spread across 8-9 Excel files. We faced a big issue: the dashboard was loading too slowly, which made it hard for client to use the data effectively. Here’s how we fixed it:

𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬:
1. The dashboard used detailed calculations in DAX that took a long time to process.
2. The dashboard had many visuals, which slowed down its performance.

𝐒𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐬:
1. I used variables within DAX to store intermediate results, reducing unnecessary calculations.
2. Removed unnecessary columns.
3. Implemented a star schema design to simplify relationships and improve query performance.
4. Limited the number of visuals on each report page.
5. Utilized bookmarks and drill-through pages to provide detailed insights without overcrowding the main dashboard.
6. Set up incremental data refresh to update only new or changed data, significantly reducing refresh time.

𝐑𝐞𝐦𝐞𝐦𝐛𝐞𝐫 𝐭𝐡𝐞𝐬𝐞 𝐩𝐨𝐢𝐧𝐭𝐬 𝐚𝐧𝐝 𝐢𝐦𝐩𝐥𝐞𝐦𝐞𝐧𝐭 𝐢𝐭 𝐢𝐧 𝐲𝐨𝐮𝐫 𝐧𝐞𝐱𝐭 𝐝𝐚𝐬𝐡𝐛𝐨𝐚𝐫𝐝. 𝐓𝐡𝐢𝐬 𝐪𝐮𝐞𝐬𝐭𝐢𝐨𝐧 𝐢𝐬 𝐚𝐥𝐬𝐨 𝐨𝐟𝐭𝐞𝐧 𝐚𝐬𝐤𝐞𝐝 𝐢𝐧 𝐈𝐧𝐭𝐞𝐫𝐯𝐢𝐞𝐰𝐬.

I have curated the best interview resources to crack Power BI Interviews 👇👇
https://topmate.io/analyst/866125

Hope you'll like it

Like this post if you need more content like this 👍❤️

How some Power BI webinars are similar to Network Marketing (MLM) webinar:

➡️ Both starts with "Join our seminar/webinar" whenever you ask any questions to them.

➡️ One makes you an entrepreneur in an hour another makes you Power BI expert in 3 hours.

➡️ In both of these webinar you will be muted so that you don't ask any questions that the host is not capable of answering.

➡️ Both targets freshers or someone who don't know how the market works.

➡️ Both runs on false promises. One promises "Daadi se pehle gaadi aur pati banne se pehle crorepati".
Another one "15 LPA as a fresher in the market just by learning Power BI"

➡️ Both shows fancy output. One in the form of rented coat suit and car and other one in the form of non-functional multi color dashboards.

➡️ One is run by a person who think entrepreneurship is all about creating a chain of 3 and another by a person who think Power BI is all about Drag and drop

Conclusion: Stay away from both.

Column vs. Table Transformations in Power Query :-

Column Transformations:

➡️ Rename: Change column names.
➡️ Change Data Type: Adjust column data types.
➡️ Add Custom Column: Create new columns with formulas.
➡️ Remove Columns: Delete unnecessary columns.
➡️ Split Column: Divide a column into multiple columns.
➡️ Merge Columns: Combine multiple columns into one.
➡️ Replace Values: Change specific values within a column.

Table Transformations:

➡️ Remove Rows: Delete specific rows.
➡️ Filter Rows: Keep or exclude rows based on conditions.
➡️ Group By: Aggregate data by grouping rows.
➡️ Pivot Column: Turn column values into multiple columns.
➡️ Unpivot Columns: Convert columns into rows.
➡️ Sort Rows: Arrange rows in a specific order.
➡️ Append Queries: Combine tables vertically.
➡️ Merge Queries: Combine tables based on common columns.

Column transformations focus on individual columns, while table transformations involve the entire table or groups of rows and columns.

Broad question, split into micro questions, group micro questions.

Now plan each page.

Start with the high-level stuff.

That should be the first page users land on.

Even in 2024, most businesses are desperate for even the most basic reporting.

Most users won't get past the headline page—that's the truth.

But for those who want a deeper dive, create pages that answer questions associated with each group of micro questions.

Want to know the most valuable trade secret?

Don't spend too long doing any of the above.

Get the basics down and get it into the hands of your users ASAP.

They'll tell you how useful it is, what could be better, and whether they'd use it or not.

Be open to feedback, use it, and iterate.

Don't overwhelm users and stick to the most basic functionality first, and build up.

That's the key to effective dashboard creation.

That's it.

Dashboards are undeniably a huge part of data work in 2024.

It's so easy to get carried away with pretty visuals and informative tables.

That's a one-way ticket to user burnout.

Stick to the above, and you won't go far wrong.