Web data import in Power BI - Practice Problems & Coding Challenges

Challenge - 5 Problems

🧠 Conceptual

intermediate

Understanding Web Data Import Authentication

You want to import data from a web API that requires authentication. Which method should you use in Power BI to securely connect and import the data?

A Use the Web connector with anonymous access and include credentials in the URL query string.

B Use the Web connector and select the appropriate authentication method like Basic or OAuth in the credentials prompt.

C Use the Web connector with no authentication and hope the API allows public access.

D Download the data manually and import it as a CSV file instead of using the Web connector.

💡 Hint

Think about how Power BI handles secure connections and credentials for web sources.

Power BI's Web connector supports various authentication methods. Selecting the correct authentication type ensures secure and successful data import.

❓ dax_lod_result

intermediate

DAX Measure for Counting Web Import Refreshes

You have a table 'WebRefreshLog' with a column 'RefreshDateTime' recording each time the web data import refreshes. Write a DAX measure to count how many refreshes happened in the last 7 days.

Power BI

RefreshCountLast7Days = CALCULATE(COUNTROWS(WebRefreshLog), FILTER(WebRefreshLog, WebRefreshLog[RefreshDateTime] >= TODAY() - 7))

A RefreshCountLast7Days = CALCULATE(COUNTROWS(WebRefreshLog), FILTER(WebRefreshLog, WebRefreshLog[RefreshDateTime] >= TODAY() - 7))

B RefreshCountLast7Days = CALCULATE(COUNTROWS(WebRefreshLog), WebRefreshLog[RefreshDateTime] >= TODAY() - 7)

C RefreshCountLast7Days = COUNTROWS(FILTER(WebRefreshLog, WebRefreshLog[RefreshDateTime] >= TODAY() - 7))

D RefreshCountLast7Days = COUNTROWS(WebRefreshLog) - 7

💡 Hint

Remember that CALCULATE changes filter context and FILTER creates a table to filter on.

Option A correctly uses CALCULATE with FILTER to count rows where the refresh date is within the last 7 days.

❓ visualization

advanced

Best Visualization for Web Data Import Status Over Time

You want to create a dashboard visual showing the success or failure of web data imports over the past month, updated daily. Which visualization type best shows trends and status clearly?

A A line chart with two lines: one for success count and one for failure count per day.

B A table listing each refresh date and its status.

C A pie chart showing total success vs failure counts for the month.

D A clustered bar chart showing counts of success and failure by day.

💡 Hint

Think about how to best show trends over time with multiple categories.

A line chart with separate lines for success and failure counts per day clearly shows trends and comparisons over time.

🔧 Formula Fix

advanced

Debugging Web Data Import Query Failure

Your Power BI web data import query fails with an error: "Access denied". You confirmed the URL and credentials are correct. What is the most likely cause?

A The Power BI desktop version is outdated and cannot connect to web sources.

B The URL is missing the https:// prefix.

C The web API requires a user-agent header that Power BI is not sending by default.

D The data source is too large to import via web connector.

💡 Hint

Think about common web API security requirements beyond credentials.

Many web APIs require specific headers like user-agent for access. Without them, the server may deny access even if credentials are correct.

❓ data_modeling

expert

Modeling Web Data Import Logs for Performance Analysis

You have imported web data logs with columns: 'ImportID', 'StartTime', 'EndTime', 'Status'. You want to analyze average import duration by status and filter by date ranges efficiently. Which data model design is best?

A Create a calculated column 'Duration' as EndTime - StartTime; use EndTime as the only date filter column without a Date table.

B Create a measure to calculate duration on the fly as EndTime - StartTime; no Date table needed because filtering is done on StartTime column directly.

C Store duration externally and import it as a column; use StartTime as text for filtering to improve performance.

D Create a calculated column 'Duration' as EndTime - StartTime and use it in measures; add a separate Date table linked to StartTime for filtering.

💡 Hint

Think about best practices for time calculations and filtering in Power BI models.

Calculated columns for duration allow easy aggregation. A separate Date table linked to StartTime enables efficient and flexible date filtering.