Power Bi Interview Questions On Dax
Top Power BI Interview Questions on DAX
Power Bi Interview Questions On Dax
In a Power BI interview, candidates may be asked a variety of questions related to Data Analysis Expressions (DAX), which is a formula language used in Power BI for creating custom calculations and aggregations. Some common interview questions related to DAX may include explaining the difference between calculated columns and measures, demonstrating how to use DAX functions to create calculated columns or measures, identifying common DAX functions like SUM, CALCULATE, and RELATED, and explaining concepts such as context transition and filter context in DAX calculations. It is recommended for candidates to have a strong understanding of DAX syntax and functions, as well as practical experience in building DAX formulas in Power BI for effective data analysis and reporting.
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1 - What is DAX and how is it different from Excel functions?
DAX stands for Data Analysis Expressions and is a formula language used in Power BI to create custom calculations in tables and matrices. DAX functions are more powerful and sophisticated compared to Excel functions as they are optimized for data analysis and retrieval in tabular data models.
2) Explain the difference between calculated columns and measures in Power BI.
Calculated columns are static columns added to a table that calculate a value for each row in the table, while measures are dynamic calculations based on the context of the data being displayed and are used in aggregations and calculations in reports.
3) How do you create a calculated column in Power BI using DAX?
To create a calculated column in Power BI, you can go to the Data view, select the table you want to add the column to, click on New Column in the Modeling tab, and enter a DAX formula to define the calculation for the new column.
4) What is the difference between a calculated column and a measure in DAX?
Calculated columns are computed at the row level in the data model and are stored in the database, increasing the size of the dataset, while measures are computed based on the context of the visualization and are not stored in the data model, thus reducing the dataset size and improving performance.
5) How do you use DAX to calculate year to date (YTD) sales in Power BI?
To calculate YTD sales in Power BI using DAX, you can create a measure that sums the sales amount for the dates from the beginning of the year up to the selected date using the TOTALYTD function or by creating a custom DAX formula that filters the data accordingly.
6) What are the different DAX functions that can be used for time intelligence calculations in Power BI?
Some common DAX functions used for time intelligence calculations in Power BI include TOTALYTD, SAMEPERIODLASTYEAR, DATESYTD, DATEADD, and CALENDAR.
7) How can you implement conditional logic in DAX formulas in Power BI?
You can implement conditional logic in DAX formulas using functions like IF, SWITCH, and SELECTEDVALUE to evaluate conditions and return different results based on the specified criteria, allowing for dynamic calculations and data analysis.
8) How do you handle errors in DAX formulas in Power BI?
You can handle errors in DAX formulas by using functions like IFERROR or ISERROR to check for errors in the calculation and return a specified value or message in case of an error, ensuring the smooth execution of the formula.
9) What is the role of context transition in DAX and how does it affect calculations in Power BI?
Context transition in DAX is the process of changing the context in which calculations are evaluated from row context to filter context or vice versa, affecting how calculations interact with the filter context and influencing the results of the calculations in Power BI reports.
10) How can you optimize DAX calculations for better performance in Power BI?
To optimize DAX calculations for better performance in Power BI, you can minimize the use of calculated columns, remove unnecessary columns from the data model, use SUMX instead of iterating functions like ROW, and avoid using complex nested functions that may slow down query execution. Additionally, using proper data modeling techniques and creating efficient relationships between tables can also improve the performance of DAX calculations in Power BI.
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