Microsoft Power BI | Tableau | Data Visualization टेलीग्राम पोस्ट

Power BI Interview Questions Asked hashtag#Bajaj Auto Ltd
1st Round

1. Self Introduction
2. What are your roles and responsibilities of your project?
3. Difference between Import Mode and Direct Mode?
4. What kind of projects have you worked on Domain?
5. How do you handle complex data transformations in Power Query? Can you provide an example of a challenging transformation you implemented?
6. What challenges you faced while doing a projects?
7. Types of Refreshes in Power BI?
8. What is DAX in Power BI?
9. How do you perform data cleansing and transformation in Power BI?
10. How do you connect to data sources in Power BI?
11. What are the components in Power BI?
12. What is Power Pivot will do in Power BI?
13. Write a query to fetch top 5 employees having highest salary?
14. Write a query to find 2nd highest salary from employee table?
15. Difference between Rank function & Dense Rank function in SQL?
16. Difference between Power BI Desktop & Power BI Service?
17. How will you optimize Power BI reports?
18. What are the difficulties you have faced when doing a projects?
19. How can you optimize a SQL query?
20. What is Indexes?
21. How ETL process happen in Power BI?
22. What is difference between Star schema & Snowflake schema and how will know when to use which schemas respectively?
23. How will you perform filtering & it's types?
24. What is Bookmarks?
25. Difference between Drilldown and Drill through in Power BI?
26. Difference between Calculated column and measure?
27. Difference between Slicer and Filter?
28. What is a use Pandas, Matplotlib, seaborn Libraries?
29. Difference between Sum and SumX?
30. Do you have any questions?

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In Power BI interviews, companies often ask scenario-based questions to test your practical knowledge. Below, I am sharing a list of some top real-world Power BI scenario-based interview questions. These will help you understand what to expect and prepare effectively for your next Power BI interview:

1. How would you visualize the relationship between 'Customer Age' and 'Purchase Amount'? What type of chart would you use and why?

2. When would you prefer a measure over a calculated column in Power BI? Provide a real-world example.

3. For a dataset containing monthly sales and marketing spend, which type of chart would best illustrate their correlation, and why?

4. How would you create a hierarchical filter for Region → Country → City in Power BI?

5. How would you allow users to interactively filter sales data by regions and product categories in a Power BI dashboard?

6. How would you enable users to toggle dynamically between different metrics (e.g., Sales, Profit, Expenses) in a single Power BI visual?

7. If a Power BI report with millions of rows is slow, what steps would you take to optimize its performance?

8. How would you display key performance indicators (KPIs) such as Total Revenue and Profit Margin in Power BI?

9. How can you build a real-time dashboard in Power BI to track order statuses or IoT sensor data?

10. How would you handle missing or null values in Power BI to ensure accurate reporting?

11. How would you visualize sales trends over time and forecast future values in Power BI?

12. How would you restrict users' access to data so they can only view the sales data for their specific region?

13. How would you highlight low-profit products in Power BI using conditional formatting?

14. How would you create a drillthrough page in Power BI to analyze customer-specific details?

15. How would you clean and transform messy data with duplicate rows and inconsistent formats in Power BI?

16. How would you create a dynamic filter to display data for the last 7 days in a Power BI report?

17. How would you compare target vs. actual sales and visualize the variance in Power BI?

18. How can you set up real-time alerts in Power BI for specific KPIs (e.g., profit margin falling below 10%)?

19. How would you calculate and display a weighted average in Power BI?

20. How would you handle matching customer addresses with slight variations (e.g., abbreviations) in Power BI?

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Master Power BI for Data Analytics: Step-by-Step

Ready to become a Power BI expert? This learning path covers all the essential skills & techniques to excel in data analytics with Power BI:

📊Introduction to Power BI:

- Overview of Power BI & its components: Power BI Desktop, Service & Mobile
- Installing & setting up Power BI Desktop
- Understanding the Power BI interface & navigation
- Connecting to various data sources: Excel, SQL databases, web data, etc.

📊Data Preparation & Transformation:

- Importing & cleaning data in Power BI
- Using Power Query for data transformation
- Data shaping & combining data from multiple sources
- Handling missing values & data inconsistencies

📊Data Modeling:

- Creating relationships between tables
- Understanding & implementing DAX
- Using calculated columns & measures
- Building & managing a star schema

📊Data Visualization:

- Creating & customizing various visualizations: bar charts, line charts, pie charts, etc.
- Using advanced visuals: maps, treemaps, scatter plots & more
- Implementing slicers & filters for interactive reports
- Designing & formatting reports for better readability

📊Advanced Data Analysis:

- Time intelligence in Power BI: YTD, QTD, MTD calculations
- Performing advanced calculations with DAX
- Using what-if parameters & scenario analysis
- Implementing R & Python scripts in Power BI for advanced analytics

📊Power BI Dashboards:

- Designing interactive dashboards for business insights
- Combining multiple reports into a single dashboard
- Using tiles, widgets & KPIs to enhance dashboards
- Best practices for dashboard design & layout

📊Power BI Service & Sharing:

- Publishing reports to Power BI Service
- Configuring data refresh schedules
- Sharing dashboards & reports with colleagues & stakeholders
- Managing roles & permissions for data security

📊Power BI Advanced Features:

- Using Power BI AI visuals: Key Influencers, Decomposition Tree etc.
- Implementing row-level security (RLS) in your data models
- Power BI apps & workspaces
- Integrating Power BI with other Microsoft services like Azure & SharePoint

📊Real-world Projects & Case Studies:

- Analyzing sales & marketing data for business insights
- Creating financial & budgetary report
- Developing customer segmentation analysis
- Building performance monitoring dashboard

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Master Power BI with this Cheat Sheet🔥

If you're preparing for a Power BI interview, this cheat sheet covers the key concepts and DAX commands you'll need. Bookmark it for last-minute revision!

📝 𝗣𝗼𝘄𝗲𝗿 𝗕𝗜 𝗕𝗮𝘀𝗶𝗰𝘀:

DAX Functions:

- SUMX: Sum of values based on a condition.
- FILTER: Filter data based on a given condition.
- RELATED: Retrieve a related column from another table.
- CALCULATE: Perform dynamic calculations.
- EARLIER: Access a column from a higher context.
- CROSSJOIN: Create a Cartesian product of two tables.
- UNION: Combine the results from multiple tables.
- RANKX: Rank data within a column.
- DISTINCT: Filter unique rows.

Data Modeling:

- Relationships: Create, manage, and modify relationships.
- Hierarchies: Build time-based hierarchies (e.g., Date, Month, Year).
- Calculated Columns: Create calculated columns to extend data.
- Measures: Write powerful measures to analyze data effectively.

Data Visualization:

- Charts: Bar charts, line charts, pie charts, and more.
- Table & Matrix: Display tabular data and matrix visuals.
- Slicers: Create interactive filters.
- Tooltips: Enhance visual interactivity with tooltips.
- Map: Display geographical data effectively.

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✅ Use DAX for efficient data analysis.

✅ Optimize data models for performance.

✅ Utilize drill-through and drill-down for deeper insights.

✅ Leverage bookmarks for enhanced navigation.

✅ Annotate your reports with comments for clarity.

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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*

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Hey guys,

Today, I curated a list of essential Power BI interview questions that every aspiring data analyst should be prepared to answer 👇👇

1. What is Power BI?

Power BI is a business analytics service developed by Microsoft. It provides tools for aggregating, analyzing, visualizing, and sharing data. With Power BI, users can create dynamic dashboards and interactive reports from multiple data sources.

Key Features:
- Data transformation using Power Query
- Powerful visualizations and reporting tools
- DAX (Data Analysis Expressions) for complex calculations

2. What are the building blocks of Power BI?

The main building blocks of Power BI include:
- Visualizations: Graphical representations of data (charts, graphs, etc.).
- Datasets: A collection of data used to create visualizations.
- Reports: A collection of visualizations on one or more pages.
- Dashboards: A single page that combines multiple visualizations from reports.
- Tiles: Single visualization found on a report or dashboard.

3. What is DAX, and why is it important in Power BI?

DAX (Data Analysis Expressions) is a formula language used in Power BI for creating custom calculations and aggregations. DAX is similar to Excel formulas but offers much more powerful data manipulation capabilities.

Tip: Be ready to explain not just the syntax, but scenarios where DAX is essential, such as calculating year-over-year growth or creating dynamic measures.

4. How does Power BI differ from Excel in data visualization?

While Excel is great for individual analysis and data manipulation, Power BI excels in handling large datasets, creating interactive dashboards, and sharing insights across the organization. Power BI also integrates better and allows for real-time data streaming.

5. What are the types of filters in Power BI, and how are they used?

Power BI offers several types of filters to refine data and display only what’s relevant:

- Visual-level filters: Apply filters to individual visuals.
- Page-level filters: Apply filters to all the visuals on a report page.
- Report-level filters: Apply filters to all pages in the report.

Filters help to create more customized and targeted reports by narrowing down the data view based on specific conditions.

6. What are Power BI Desktop, Power BI Service, and Power BI Mobile? How do they interact?

- Power BI Desktop: A desktop-based application used for data modeling, creating reports, and building dashboards.
- Power BI Service: A cloud-based platform that allows users to publish and share reports created in Power BI Desktop.
- Power BI Mobile: Allows users to view reports and dashboards on mobile devices for on-the-go access.

These components work together in a typical workflow:
1. Build reports and dashboards in Power BI Desktop.
2. Publish them to the Power BI Service for sharing and collaboration.
3. View and interact with reports on Power BI Mobile for easy access anywhere.

7. Explain the difference between calculated columns and measures.

- Calculated columns are added to a table using DAX and are calculated row by row.
- Measures are calculations used in aggregations, such as sums, averages, and ratios. Unlike calculated columns, measures are dynamic and evaluated based on the filter context of a report.

8. How would you perform data cleaning and transformation in Power BI?

Data cleaning and transformation in Power BI are mainly done using Power Query Editor. Here, you can:
- Remove duplicates or empty rows
- Split columns (e.g., text into multiple parts)
- Change data types (e.g., text to numbers)
- Merge and append queries from different data sources

Power BI isn’t just about visuals; it’s about turning raw data into actionable insights. So, keep honing your skills, try building dashboards, and soon enough, you’ll be impressing your interviewers too!

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