Scheduled data refresh in Power BI - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Scheduled Refresh Frequency

You have a Power BI dataset connected to an on-premises SQL Server database. You want the data to update automatically every 4 hours. Which setting should you configure in the Power BI service?

A Set the scheduled refresh frequency to 'Monthly' and specify the date.

B Set the scheduled refresh frequency to 'Weekly' and select the days you want refreshes.

C Set the scheduled refresh frequency to 'Hourly' and specify every 4 hours.

D Set the scheduled refresh frequency to 'Daily' and specify 4 refresh times per day.

💡 Hint

Think about how to schedule multiple refreshes within a day.

Power BI allows up to 8 scheduled refreshes per day. To refresh every 4 hours, you set the frequency to daily and specify 4 refresh times spaced 4 hours apart.

❓ dax_lod_result

intermediate

DAX Measure Behavior After Scheduled Refresh

You have a DAX measure that calculates total sales for the current month using the formula:
Total Sales MTD = CALCULATE(SUM(Sales[Amount]), DATESMTD(Calendar[Date]))
After a scheduled refresh at midnight, what will be the value of Total Sales MTD at 1 AM on the first day of the month?

A Zero, because no sales have occurred yet in the new month.

B The sum of sales from the first day of the month up to 1 AM (including any sales recorded at that time).

C The total sales for the entire previous month.

D An error because the data model is not updated yet.

💡 Hint

Consider what data is available immediately after midnight.

At 1 AM on the first day of the month, no sales have occurred yet in the new month, so the measure returns zero. The scheduled refresh updates the data model to the latest data, but no new sales exist yet for the current month.

🔧 Formula Fix

advanced

Troubleshooting Scheduled Refresh Failure

Your Power BI dataset refresh fails with the error: 'Data source credentials are invalid'. You have recently changed the password for the SQL Server account used in the data source settings. What is the best way to fix this issue?

A Change the password back to the old one to match the stored credentials.

B Recreate the dataset from scratch with the new credentials.

C Update the data source credentials in the Power BI service with the new password.

D Disable scheduled refresh and refresh the dataset manually.

💡 Hint

Think about where Power BI stores credentials for scheduled refresh.

When credentials change, you must update them in the Power BI service under data source settings to allow scheduled refresh to connect successfully.

❓ visualization

advanced

Designing a Refresh Status Dashboard

You want to create a Power BI report page that shows the status of scheduled refreshes for multiple datasets. Which visual and data approach best communicates the refresh success or failure over the past week?

A Use a pie chart showing the percentage of datasets that refreshed successfully versus failed in the last week.

B Use a table visual listing datasets with columns for last refresh date, status (success/failure), and duration, filtered for the last 7 days.

C Use a line chart showing the number of refreshes per day without status details.

D Use a card visual showing the total number of datasets refreshed in the last week.

💡 Hint

Think about what details help identify issues quickly.

A table with dataset names, last refresh date, status, and duration provides clear, detailed information to monitor refresh health and troubleshoot failures.

🎯 Scenario

expert

Optimizing Scheduled Refresh for Large Datasets

Your Power BI report uses a large dataset that takes 3 hours to refresh. You want to minimize downtime and keep data as fresh as possible. Which strategy is best to achieve this?

A Use incremental refresh to update only recent data partitions and schedule refreshes during off-peak hours.

B Increase the refresh frequency to every hour to reduce data latency.

C Disable scheduled refresh and refresh the dataset manually once a week.

D Split the dataset into multiple smaller datasets and refresh them all simultaneously.

💡 Hint

Think about how to reduce refresh time and resource use.

Incremental refresh updates only new or changed data, reducing refresh time and resource consumption. Scheduling during off-peak hours minimizes impact on users.