Prepare for your next data analyst interview by reviewing essential concepts in Power BI, DAX, SQL, and data modeling. This quiz covers foundational knowledge, best practices, and scenario-based questions relevant for data analysis roles and business intelligence projects.
Which platform is primarily used for creating reports and data models in Power BI?
Explanation: Power BI Desktop is designed for developing reports, performing data modeling, and creating DAX calculations. Power BI Service is mainly used for publishing, sharing, and collaborative features in the cloud. Power BI Mobile is intended for viewing reports on mobile devices. Power View is an older data visualization tool, not the main development environment.
When building a data model in Power BI, why is the Star Schema preferred over the Snowflake Schema?
Explanation: The Star Schema allows for simpler relationships and often improves query speed in Power BI. Using this schema makes your model easier to understand and optimize. Snowflake Schema involves more normalization, leading to complex joins and slower performance. The other options either incorrectly attribute complexity or storage usage.
For calculating a year-over-year sales comparison in Power BI, which DAX function is commonly used?
Explanation: SAMEPERIODLASTYEAR is a time intelligence DAX function that helps compare data from the same period in the previous year. TOPN is used for sorting and retrieving top rows, CONCATENATE joins text values, and COUNTROWS counts rows in a table. The distractors do not handle time-based comparisons.
Which action is recommended to improve the performance of a slow Power BI report with a large dataset?
Explanation: Reducing unnecessary columns and rows at the data source limits the data Power BI needs to process, resulting in faster reports. Using only calculated columns can slow performance due to heavy calculation load. Adding complex visuals strains the report, making it slower. Flat tables increase complexity and are less efficient compared to optimized schemas.
Which DAX function is used for ranking values, such as ranking products by sales?
Explanation: RANKX is designed to rank items, such as sales by product or region. SUMMARIZE is used for grouping data, REMOVEFILTERS adjusts filters, and CALCULATETABLE creates new tables with filter context applied. These other functions do not provide ranking capabilities.
How does Row Level Security (RLS) help in Power BI reports shared with multiple users?
Explanation: Row Level Security restricts what data users can view by assigning role-based filters, ensuring each user only sees authorized data. It does not encrypt data, which is managed separately, nor does it directly influence refresh speed or report themes.
Which SQL operation would you use to combine customer information from two tables in preparation for reporting?
Explanation: JOIN operations combine data from two or more tables based on a related column, essential for integrating datasets before loading into reporting tools. PRINT is for displaying output messages, DELETE removes records, and RAND generates random numbers—none of which combine table data.
Before loading data into Power BI, which step can help reduce model size and improve performance?
Explanation: Eliminating unused columns reduces the data volume, making the Power BI model more efficient and faster. Increasing visuals or redundant relationships adds complexity without performance benefits, and splitting tables for every field causes unnecessary fragmentation.
Which DAX function can help calculate the Year-To-Date total sales?
Explanation: TOTALYTD calculates the running total for a measure from the start of the year to a specific date, commonly used for Year-To-Date analysis. DISTINCTCOUNT counts unique values, FORMAT changes the display format, and EARLIER is used in row contexts but does not aggregate year-to-date values.
When explaining a complex dashboard to a non-technical manager, what approach is most effective?
Explanation: Translating technical results into business value and using easy-to-understand language helps non-technical audiences grasp dashboard outcomes. Describing DAX formulas or raw data in detail may cause confusion, and discussing the data model's structure is often too technical for business-focused audiences.
What is a main advantage of using Incremental Refresh in Power BI for large datasets?
Explanation: Incremental Refresh allows Power BI to update just the new or modified records, saving time and computing resources. It does not create visuals, dashboards, or apply machine learning; its primary purpose is efficient data refresh management.
If you want to ignore all filters on a column except one, which DAX function should you use?
Explanation: ALLEXCEPT keeps filters on specified columns but ignores others, useful for calculations that require maintaining certain contexts. ALL removes all filters, IF performs logical checks, and MINX is an iterator for finding minimums, so they are not suitable for this task.
Why is it important to remove unnecessary visuals from a Power BI dashboard?
Explanation: Removing unnecessary visuals streamlines report performance and makes dashboards easier to interpret. Increasing data volume or intentionally complicating the design hinders usability, while hiding errors is not a legitimate practice for data visualization.
Which SQL clause would most likely be used to summarize sales by region before importing into Power BI?
Explanation: GROUP BY allows you to aggregate data, such as calculating total sales per region, making it ready for dashboarding. ORDER BY only sorts results, EXCEPT compares two result sets, and HAVOC is not a valid SQL keyword.
How does Object-Level Security differ from Row Level Security in Power BI?
Explanation: Object-Level Security provides control over visibility of different tables or columns for users, while Row Level Security works at the individual row level. Encryption is not handled by this feature, and sharing with anonymous users is managed in other security settings.
If key data for a requested KPI is missing, what should a data analyst do?
Explanation: Communicating data issues, proposing workarounds, and transparently documenting limitations ensure stakeholders make informed decisions. Ignoring issues, making guesses, or starting over without rationale can lead to misleading insights and project problems.