This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Model the data (25–30%)
   --> Design and implement a data model
      --> Create a Common Date Table

Below are 10 practice questions (with answers and explanations) for this topic of the exam.
There are also 2 practice tests for the PL-300 exam with 60 questions each (with answers) available on the hub.

Practice Questions

Question 1

Why is creating a common date table recommended instead of using date columns directly from fact tables?

A. It reduces dataset size
B. It improves report rendering speed
C. It enables reliable time-intelligence calculations
D. It automatically creates relationships

✅ Correct Answer: C

Explanation:
DAX time-intelligence functions require a proper date table with contiguous dates. Using fact table date columns often leads to incorrect or blank results.

Question 2

Which requirement must be met for a table to be marked as a Date table in Power BI?

A. It must contain a Year column
B. It must contain a unique, contiguous Date column
C. It must be created using DAX
D. It must be hidden from report view

✅ Correct Answer: B

Explanation:
A valid date table must contain a single column of unique dates with no gaps. This column is selected when marking the table as a Date table.

Question 3

What happens if a date table is not marked as a Date table?

A. Relationships are disabled
B. Time-intelligence functions may not work correctly
C. Measures cannot be created
D. The model refresh fails

✅ Correct Answer: B

Explanation:
Marking a table as a Date table enables Power BI to correctly evaluate time-intelligence functions like TOTALYTD and SAMEPERIODLASTYEAR.

Question 4

Which DAX function is commonly used to create a date table?

A. DATEADD
B. DATATABLE
C. CALENDAR
D. FORMAT

✅ Correct Answer: C

Explanation:
The CALENDAR() function generates a continuous date range, making it ideal for creating date tables in DAX.

Question 5

A fact table contains Order Date and Ship Date columns. What is the recommended modeling approach?

A. Use one date table with two inactive relationships
B. Use auto date/time for both columns
C. Duplicate the date table for each role
D. Merge the two date columns

✅ Correct Answer: C

Explanation:
Duplicating the date table creates role-playing dimensions, allowing both relationships to remain active and slicers to work intuitively.

Question 6

Which attribute is least likely to be included in a common date table?

A. Month Name
B. Quarter
C. Customer ID
D. Fiscal Year

✅ Correct Answer: C

Explanation:
A date table contains time-related attributes only. Customer ID belongs in a customer dimension.

Question 7

Why is Auto Date/Time generally discouraged in enterprise Power BI models?

A. It increases refresh times
B. It limits customization and control
C. It disables relationships
D. It prevents DAX calculations

✅ Correct Answer: B

Explanation:
Auto Date/Time creates hidden tables that lack flexibility and are not ideal for advanced time-intelligence scenarios.

Question 8

Which relationship configuration is most appropriate between a date table and a fact table?

A. One-to-one with bi-directional filtering
B. One-to-many with single-direction filtering
C. Many-to-many with bi-directional filtering
D. Many-to-one with bi-directional filtering

✅ Correct Answer: B

Explanation:
The date table should be on the one-side, filtering the fact table via single-direction filtering, consistent with star schema design.

Question 9

What is a common mistake when creating a date table?

A. Including fiscal columns
B. Extending the date range beyond the fact data
C. Leaving gaps in the date sequence
D. Using Power Query

✅ Correct Answer: C

Explanation:
Date tables must contain continuous dates. Gaps can break time-intelligence calculations.

Question 10

Which scenario most strongly indicates the need for a common date table?

A. Reports with only categorical data
B. Models without relationships
C. Reports using year-over-year comparisons
D. Importing a single Excel table

✅ Correct Answer: C

Explanation:
Year-over-year and other time-based comparisons depend on a properly configured date table.

Final Exam Tips 🧠

• Always create and mark a date table
• Avoid relying on auto date/time
• Ensure dates are unique and contiguous
• Use role-playing dimensions for multiple date fields
• Think “time intelligence” whenever dates appear in a question

Go back to the PL-300 Exam Prep Hub main page

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Model the data (25–30%)
   --> Design and implement a data model
      --> Identify Use Cases for Calculated Columns and Calculated Tables

Below are 10 practice questions (with answers and explanations) for this topic of the exam.
There are also 2 practice tests for the PL-300 exam with 60 questions each (with answers) available on the hub.

Practice Questions

Question 1

You need to concatenate First Name and Last Name for use in a slicer. Which solution is most appropriate?

A. Measure
B. Calculated column
C. Calculated table
D. Power Query parameter

✅ Correct Answer: B

Explanation:
Slicers require columns, not measures. A calculated column performs row-level logic and is evaluated at refresh.

Question 2

A calculation must respond dynamically to report filters and slicers. Which option should you choose?

A. Calculated column
B. Calculated table
C. Measure
D. Power Query step

✅ Correct Answer: C

Explanation:
Measures are evaluated at query time and respond to filter context, unlike calculated columns or tables.

Question 3

You need to create a reusable calendar table using DAX. Which object should you create?

A. Measure
B. Calculated column
C. Calculated table
D. Power Query column

✅ Correct Answer: C

Explanation:
Calculated tables return entire tables and are commonly used to create date dimensions.

Question 4

Which scenario is best suited for a calculated column rather than a measure?

A. Total sales
B. Year-to-date revenue
C. Product price category
D. Average discount rate

✅ Correct Answer: C

Explanation:
Categorizing each row (e.g., Low / Medium / High) is a row-level operation, making a calculated column appropriate.

Question 5

Why should calculated columns be used sparingly?

A. They don’t support DAX
B. They increase model size
C. They can’t be sorted
D. They break relationships

✅ Correct Answer: B

Explanation:
Calculated columns are stored in the model, increasing memory usage and refresh time.

Question 6

Which scenario most strongly indicates a calculated table?

A. Creating a dynamic ranking
B. Generating a disconnected slicer table
C. Summing sales by category
D. Calculating profit margin

✅ Correct Answer: B

Explanation:
Disconnected slicers and parameter tables are common use cases for calculated tables.

Question 7

A user expects a calculated column to change when a slicer is applied. Why does this not happen?

A. Calculated columns use row context
B. Calculated columns require USERELATIONSHIP
C. Calculated columns evaluate at refresh
D. Calculated columns cannot reference measures

✅ Correct Answer: C

Explanation:
Calculated columns are computed during data refresh and do not respond to filter context.

Question 8

Which option is NOT an appropriate use of a calculated table?

A. Creating a bridge table
B. Creating a what-if parameter
C. Creating a static lookup table
D. Creating a dynamic aggregation

✅ Correct Answer: D

Explanation:
Dynamic aggregations should be handled by measures, not calculated tables.

Question 9

You need a column to sort month names chronologically. What should you create?

A. Measure
B. Calculated column
C. Calculated table
D. Aggregation table

✅ Correct Answer: B

Explanation:
Sorting requires a column. A calculated column (e.g., MonthNumber) supports Sort by Column.

Question 10

Which modeling decision best improves performance?

A. Replacing measures with calculated columns
B. Using calculated tables for all dimensions
C. Moving row-level logic to Power Query
D. Adding more calculated columns

✅ Correct Answer: C

Explanation:
Power Query transformations occur before loading and do not increase DAX complexity or model memory usage.

Final Exam Reminders 🧠

• Columns = row-level, static
• Tables = structure, relationships, parameters
• Measures = dynamic, aggregation
• Power Query = preferred for data shaping

Go back to the PL-300 Exam Prep Hub main page

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Model the data (25–30%)
   --> Create model calculations by using DAX
      --> Create single aggregation measures

Below are 10 practice questions (with answers and explanations) for this topic of the exam.
There are also 2 practice tests for the PL-300 exam with 60 questions each (with answers) available on the hub.

Practice Questions

Question 1

You need a measure that calculates total sales amount and responds to report slicers. Which DAX expression should you use?

A. Total Sales = Sales[SalesAmount]
B. Total Sales = SUM(Sales[SalesAmount])
C. Total Sales = CALCULATE(Sales[SalesAmount])
D. Total Sales = SUMX(Sales, Sales[SalesAmount])

✅ Correct Answer: B

Explanation:
SUM() is the correct single aggregation function for adding numeric values in a column. It automatically responds to filter context. SUMX() is unnecessary for simple aggregations.

Question 2

Which function should you use to count the total number of rows in a fact table?

A. COUNT()
B. COUNTA()
C. COUNTROWS()
D. SUM()

✅ Correct Answer: C

Explanation:
COUNTROWS() counts rows in a table regardless of column values and is the preferred approach for counting records in fact tables.

Question 3

A column contains text values and blanks. You want to count the number of non-blank entries. Which function should you use?

A. COUNT()
B. COUNTA()
C. COUNTROWS()
D. SUM()

✅ Correct Answer: B

Explanation:
COUNTA() counts non-blank values across all data types, including text, making it ideal for this scenario.

Question 4

Why should aggregation logic typically be implemented as a measure rather than a calculated column?

A. Measures consume more memory
B. Measures are evaluated at data refresh
C. Measures respond to filter context
D. Calculated columns are faster at query time

✅ Correct Answer: C

Explanation:
Measures are evaluated at query time and dynamically respond to slicers, filters, and visuals. Calculated columns are static and do not react to user interaction.

Question 5

Which aggregation function returns the arithmetic mean of a numeric column?

A. SUM()
B. AVERAGEX()
C. AVERAGE()
D. COUNT()

✅ Correct Answer: C

Explanation:
AVERAGE() performs a simple mean over a single column. AVERAGEX() is an iterator and is unnecessary for basic aggregations.

Question 6

You drag a numeric column into a visual and Power BI automatically creates a sum. What type of measure is this?

A. Calculated measure
B. Explicit measure
C. Implicit measure
D. Calculated column

✅ Correct Answer: C

Explanation:
Implicit measures are automatically generated by Power BI when a field is placed in a visual. The PL-300 exam favors explicit measures created with DAX.

Question 7

Which DAX expression correctly counts the number of orders in a Sales table?

A. Order Count = COUNT(Sales)
B. Order Count = COUNT(Sales[OrderID])
C. Order Count = COUNTROWS(Sales)
D. Order Count = COUNTA(Sales)

✅ Correct Answer: C

Explanation:
COUNTROWS() is the safest and most reliable method for counting records in a table. COUNT() requires a numeric column and may produce misleading results.

Question 8

What happens to a single aggregation measure when a slicer is applied?

A. The value remains unchanged
B. The measure recalculates based on filter context
C. The measure recalculates only at refresh
D. The measure stops working

✅ Correct Answer: B

Explanation:
Measures automatically recalculate based on the current filter context created by slicers, filters, and visuals.

Question 9

Which function returns the earliest date in a filtered context?

A. FIRSTDATE()
B. MIN()
C. EARLIEST()
D. STARTDATE()

✅ Correct Answer: B

Explanation:
MIN() returns the smallest value in a column and works correctly with dates and filter context. It is a valid single aggregation function.

Question 10

Which of the following is the best practice when creating aggregation measures for PL-300?

A. Use calculated columns whenever possible
B. Use implicit measures to save time
C. Use explicit measures with clear naming
D. Avoid formatting measures

✅ Correct Answer: C

Explanation:
Explicit measures with clear, business-friendly names are reusable, easier to maintain, and strongly aligned with PL-300 expectations.

Final Exam Tips 💡

• Expect COUNT vs COUNTROWS vs COUNTA questions
• Prefer SUM over SUMX for simple totals
• Measures always respect filter context
• Avoid calculated columns for aggregations
• Clear naming and formatting matter

Go back to the PL-300 Exam Prep Hub main page

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Model the data (25–30%)
   --> Create model calculations by using DAX
      --> Use the CALCULATE function

Below are 10 practice questions (with answers and explanations) for this topic of the exam.
There are also 2 practice tests for the PL-300 exam with 60 questions each (with answers) available on the hub.

Practice Questions

Question 1

What is the primary purpose of the CALCULATE function in DAX?

A. To iterate over a table row by row
B. To change the filter context in which an expression is evaluated
C. To create calculated columns
D. To return a table of filtered rows

✅ Correct Answer: B

Explanation:
CALCULATE evaluates an expression in a modified filter context, making it the foundation of most advanced DAX measures. Iteration and table-returning logic are handled by other functions.

Question 2

Which measure correctly calculates total sales for only the year 2024?

Total Sales = SUM(Sales[SalesAmount])

A.

CALCULATE(Sales[SalesAmount], Sales[Year] = 2024)

B.

CALCULATE([Total Sales], Sales[Year] = 2024)

C.

FILTER([Total Sales], Sales[Year] = 2024)

D.

SUMX(Sales, Sales[SalesAmount], Sales[Year] = 2024)

✅ Correct Answer: B

Explanation:
CALCULATE modifies the filter context for an expression, typically a measure like [Total Sales]. Option A is invalid syntax, and C/D misuse FILTER and SUMX.

Question 3

What happens when CALCULATE is used inside a calculated column?

A. It disables row context
B. It converts row context to filter context
C. It ignores relationships
D. It removes all filters automatically

✅ Correct Answer: B

Explanation:
This is known as context transition. CALCULATE converts the current row context into filter context, allowing aggregations to work per row.

Question 4

Which function is most appropriate to remove filters from a single column?

A. FILTER
B. ALL
C. REMOVEFILTERS
D. VALUES

✅ Correct Answer: C

Explanation:
REMOVEFILTERS(Column) explicitly removes filters from a column and is preferred for clarity in modern DAX. ALL also removes filters but returns a table.

Question 5

Which scenario requires using a FILTER() function inside CALCULATE?

A. Applying a simple equality filter
B. Removing all filters from a table
C. Applying complex row-level conditions
D. Summing a column

✅ Correct Answer: C

Explanation:
FILTER() is required when Boolean filters are insufficient, such as multi-column or calculated conditions.

Question 6

Which statement about Boolean filters in CALCULATE is TRUE?

A. They can reference multiple columns
B. They can reference measures
C. They must reference a single column
D. They must return a table

✅ Correct Answer: C

Explanation:
Boolean filter expressions in CALCULATE must reference one column only and cannot directly use measures.

Question 7

What will the following measure do?

Sales Ignore Year =
CALCULATE(
    [Total Sales],
    REMOVEFILTERS(Date[Year])
)

A. Show sales for the selected year
B. Ignore all date filters
C. Ignore only the Year filter
D. Return blank

✅ Correct Answer: C

Explanation:
Only filters on Date[Year] are removed. Other date filters (month, day) remain active.

Question 8

Which DAX pattern is most common for time intelligence calculations?

A. SUMX with FILTER
B. CALCULATE with a date function
C. A calculated column
D. A disconnected table

✅ Correct Answer: B

Explanation:
Time intelligence functions such as DATESYTD, SAMEPERIODLASTYEAR, and DATEADD are almost always used inside CALCULATE.

Question 9

Why is it recommended to create base measures before using CALCULATE?

A. Base measures improve visual formatting
B. CALCULATE cannot reference columns
C. Reusable logic simplifies complex measures
D. Base measures load faster

✅ Correct Answer: C

Explanation:
Using base measures (e.g., [Total Sales]) improves readability, maintainability, and reuse, which is a common PL-300 best practice.

Question 10

Which of the following best describes how CALCULATE handles existing filters?

A. It always removes them
B. It ignores slicers
C. It adds or overrides filters as specified
D. It applies filters only once

✅ Correct Answer: C

Explanation:
CALCULATE modifies filter context by adding new filters or overriding existing ones, depending on the filter arguments provided.

Final Exam Tips for CALCULATE (PL-300)

• Expect scenario-based questions
• Focus on filter context behavior
• Understand context transition
• Know when to use:
  • Boolean filters
  • FILTER()
  • ALL vs REMOVEFILTERS
• Assume CALCULATE is involved if logic feels “advanced”

Go back to the PL-300 Exam Prep Hub main page

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Model the data (25–30%)
   --> Create model calculations by using DAX
      --> Implement Time Intelligence Measures

Below are 10 practice questions (with answers and explanations) for this topic of the exam.
There are also 2 practice tests for the PL-300 exam with 60 questions each (with answers) available on the hub.

Practice Questions

Question 1

Which requirement must be met for built-in DAX time intelligence functions to work correctly?

A. The fact table must contain a datetime column
B. The date column must be sorted by another column
C. A continuous, marked date table must exist
D. Measures must be created as calculated columns

✅ Correct Answer: C

Explanation:
Built-in time intelligence functions require a continuous date table that is explicitly marked as a Date table. Missing dates or unmarked tables cause incorrect or blank results.

Question 2

Which measure correctly calculates Year-to-Date (YTD) sales?

A.

Sales YTD = SUM(Sales[SalesAmount])

B.

Sales YTD = DATESYTD(Sales[Date])

C.

Sales YTD =
CALCULATE(
    [Total Sales],
    DATESYTD(Date[Date])
)

D.

Sales YTD = SUMX(DATESYTD(Date[Date]), [Total Sales])

✅ Correct Answer: C

Explanation:
DATESYTD must be used inside CALCULATE to modify filter context. Options A and B are incomplete, and D is an incorrect pattern.

Question 3

Which function returns values for the same period in the previous year?

A. DATEADD
B. SAMEPERIODLASTYEAR
C. DATESYTD
D. PARALLELPERIOD

✅ Correct Answer: B

Explanation:
SAMEPERIODLASTYEAR shifts the date context back exactly one year and is commonly used for year-over-year comparisons.

Question 4

What is the main reason to use DATEADD instead of SAMEPERIODLASTYEAR?

A. It performs faster
B. It works without a date table
C. It supports flexible offsets (months, quarters, days)
D. It ignores relationships

✅ Correct Answer: C

Explanation:
DATEADD allows shifting the date context by various intervals, making it more flexible for non-year-based comparisons.

Question 5

Which measure correctly calculates rolling 12-month sales?

A.

Rolling 12M =
SUM(Sales[SalesAmount])

B.

Rolling 12M =
CALCULATE(
    [Total Sales],
    DATESINPERIOD(Date[Date], TODAY(), -12, MONTH)
)

C.

Rolling 12M =
CALCULATE(
    [Total Sales],
    DATESINPERIOD(
        Date[Date],
        MAX(Date[Date]),
        -12,
        MONTH
    )
)

D.

Rolling 12M =
DATESINPERIOD(Date[Date], -12, MONTH)

✅ Correct Answer: C

Explanation:
MAX(Date[Date]) ensures the rolling window aligns with the current evaluation context, which is essential for correct rolling calculations.

Question 6

Why is DIVIDE() recommended when calculating time-based percentage changes?

A. It is faster than /
B. It prevents circular dependencies
C. It automatically formats results
D. It safely handles divide-by-zero scenarios

✅ Correct Answer: D

Explanation:
DIVIDE() returns a safe result (blank or alternate value) instead of an error when the denominator is zero.

Question 7

Which scenario would cause a YTD measure to return incorrect results?

A. The date table contains fiscal year columns
B. The date table has missing dates
C. The measure uses CALCULATE
D. The model uses a star schema

✅ Correct Answer: B

Explanation:
Built-in time intelligence requires a complete date range with no gaps. Missing dates break time-based calculations.

Question 8

Where should time intelligence measures typically be created?

A. Calculated columns
B. Calculated tables
C. Measures
D. Power Query

✅ Correct Answer: C

Explanation:
Time intelligence calculations depend on filter context, which is only evaluated dynamically in measures.

Question 9

Which function returns all dates from the beginning of the quarter to the current context?

A. DATESMTD
B. DATESQTD
C. DATESYTD
D. DATEADD

✅ Correct Answer: B

Explanation:
DATESQTD calculates quarter-to-date values, commonly tested alongside YTD and MTD.

Question 10

What is the primary role of the date table in time intelligence?

A. Store fact data
B. Improve visual formatting
C. Control time-based filter context
D. Reduce model size

✅ Correct Answer: C

Explanation:
The date table defines the time dimension used by DAX functions to evaluate periods accurately.

Final PL-300 Exam Tips for Time Intelligence

• Always check for a marked date table
• Expect scenario-based questions
• Use built-in time intelligence functions first
• Remember that CALCULATE is always involved
• Validate measures at different time granularities

Go back to the PL-300 Exam Prep Hub main page

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Model the data (25–30%)
   --> Create model calculations by using DAX
      --> Use Basic Statistical Functions

Below are 10 practice questions (with answers and explanations) for this topic of the exam.
There are also 2 practice tests for the PL-300 exam with 60 questions each (with answers) available on the hub.

Practice Questions

Question 1

Which DAX function returns the arithmetic mean of a numeric column?

A. MEDIAN
B. AVERAGEX
C. AVERAGE
D. MEAN

✅ Correct Answer: C

Explanation:
AVERAGE calculates the arithmetic mean of a numeric column. AVERAGEX is an iterator, and MEAN is not a valid DAX function.

Question 2

You need to count the number of unique customers in a sales table. Which function should you use?

A. COUNT
B. COUNTA
C. COUNTROWS
D. DISTINCTCOUNT

✅ Correct Answer: D

Explanation:
DISTINCTCOUNT counts unique values in a column, which is required when counting unique customers or products.

Question 3

What is the primary difference between COUNT and COUNTA?

A. COUNT works on tables; COUNTA works on columns
B. COUNT counts numeric values; COUNTA counts non-blank values of any type
C. COUNT ignores blanks; COUNTA counts blanks
D. COUNT is slower than COUNTA

✅ Correct Answer: B

Explanation:
COUNT counts only non-blank numeric values, while COUNTA counts all non-blank values regardless of data type.

Question 4

Which function should you use to count the number of rows returned by a table expression?

A. COUNT
B. COUNTA
C. COUNTROWS
D. DISTINCTCOUNT

✅ Correct Answer: C

Explanation:
COUNTROWS counts the number of rows in a table and is commonly used to count records after filters are applied.

Question 5

Which measure correctly calculates the median sales amount?

A.

Median Sales = MEDIANX(Sales, Sales[SalesAmount])

B.

Median Sales = MEDIAN(Sales[SalesAmount])

C.

Median Sales = AVERAGE(Sales[SalesAmount])

D.

Median Sales = SUM(Sales[SalesAmount])

✅ Correct Answer: B

Explanation:
MEDIAN calculates the middle value of a numeric column and is less sensitive to outliers than AVERAGE.

Question 6

Which function measures how spread out values are around the mean for an entire population?

A. VAR.S
B. VAR.P
C. STDEV.S
D. MEDIAN

✅ Correct Answer: B

Explanation:
VAR.P calculates population variance. VAR.S is used for samples.

Question 7

Which DAX function returns the population standard deviation?

A. STDEV.S
B. STDEVX.P
C. STDEV.P
D. VAR.P

✅ Correct Answer: C

Explanation:
STDEV.P calculates the standard deviation for an entire population dataset.

Question 8

You need to calculate the average sales amount only for products in the “Accessories” category. Which measure is correct?

A.

AVERAGE(Sales[SalesAmount], Product[Category] = "Accessories")

B.

CALCULATE(
    AVERAGE(Sales[SalesAmount]),
    Product[Category] = "Accessories"
)

C.

FILTER(
    AVERAGE(Sales[SalesAmount]),
    Product[Category] = "Accessories"
)

D.

AVERAGEX(
    Sales,
    Product[Category] = "Accessories"
)

✅ Correct Answer: B

Explanation:
CALCULATE modifies filter context, allowing the average to be evaluated only for the specified category.

Question 9

When should you prefer MEDIAN over AVERAGE?

A. When data has missing values
B. When performance is critical
C. When data contains outliers
D. When counting rows

✅ Correct Answer: C

Explanation:
The median is less affected by extreme values and provides a better measure of central tendency when outliers exist.

Question 10

Which statement about basic statistical measures is TRUE?

A. They should be created as calculated columns
B. They ignore filter context
C. They dynamically recalculate based on filters
D. They require a date table

✅ Correct Answer: C

Explanation:
Statistical measures are filter-context aware, meaning their results change dynamically based on slicers and filters.

Final PL-300 Exam Tips for Statistical Functions

• Know the differences between COUNT, COUNTA, COUNTROWS, and DISTINCTCOUNT
• Understand when to use MEDIAN vs AVERAGE
• Be comfortable with variance and standard deviation functions
• Expect filter context–based questions using CALCULATE
• Use measures, not calculated columns

Go back to the PL-300 Exam Prep Hub main page

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Model the data (25–30%)
   --> Create model calculations by using DAX
      --> Create semi-additive measures

Below are 10 practice questions (with answers and explanations) for this topic of the exam.
There are also 2 practice tests for the PL-300 exam with 60 questions each (with answers) available on the hub.

Practice Questions

1. Identifying a Semi-Additive Measure

Question:
Which of the following metrics is most likely to require a semi-additive measure?

A. Total Sales Amount
B. Quantity Sold
C. Daily Inventory Balance
D. Total Number of Orders

Correct Answer: C

Explanation:
Inventory balance represents a snapshot in time, not an accumulated activity. Summing it across dates produces incorrect totals. Sales, quantity, and orders are fully additive across time.

2. Why SUM Produces Incorrect Results

Question:
A report sums daily account balances over a month and produces inflated totals. What is the root cause?

A. Incorrect relationships
B. Using SUM instead of a time-aware calculation
C. Missing a date hierarchy
D. Incorrect data type

Correct Answer: B

Explanation:
Account balances are semi-additive. Using SUM across time double-counts values. A time-aware calculation such as retrieving the last value is required.

3. Choosing the Correct DAX Pattern

Question:
Which DAX expression correctly returns the ending balance for a selected period?

A.

SUM(FactBalances[Balance])

B.

AVERAGE(FactBalances[Balance])

C.

CALCULATE(
    SUM(FactBalances[Balance]),
    LASTDATE('Date'[Date])
)

D.

COUNT(FactBalances[Balance])

Correct Answer: C

Explanation:
CALCULATE combined with LASTDATE ensures that only the final date in the current filter context is evaluated, which is the correct behavior for ending balances.

4. Handling Missing Dates

Question:
Some dates have no balance records. Which function ensures the last available balance is returned?

A. LASTDATE
B. FIRSTDATE
C. LASTNONBLANK
D. MAX

Correct Answer: C

Explanation:
LASTNONBLANK finds the most recent date with data, making it ideal when fact data is not recorded every day.

5. Average Over Time Scenario

Question:
You need to report the average daily inventory level for a month. Which approach is correct?

A. SUM inventory values
B. Use AVERAGE on the inventory column
C. Use AVERAGEX over the Date table
D. Use COUNT of inventory rows

Correct Answer: C

Explanation:
AVERAGEX iterates over each date, evaluating inventory per day and then averaging the results. This is the correct approach for semi-additive snapshot values.

6. Beginning Balance Requirement

Question:
Which function should be used to calculate a beginning-of-period balance?

A. LASTDATE
B. FIRSTDATE
C. MAX
D. ENDOFMONTH

Correct Answer: B

Explanation:
FIRSTDATE returns the earliest date in the current filter context, making it ideal for beginning balances.

7. Identifying Incorrect Business Logic

Question:
A measure returns correct daily balances but incorrect monthly totals. What is the most likely issue?

A. The Date table is inactive
B. The measure uses a calculated column
C. The measure is additive over time
D. Cross-filter direction is incorrect

Correct Answer: C

Explanation:
Snapshot metrics should not aggregate across time. If monthly totals are incorrect, the measure is likely being summed instead of using a semi-additive pattern.

8. Relationship to Time Intelligence

Question:
Why is a proper Date table critical for semi-additive measures?

A. It improves report performance
B. It enables slicers
C. Time intelligence functions require it
D. It reduces model size

Correct Answer: C

Explanation:
Functions like LASTDATE, FIRSTDATE, and ENDOFMONTH rely on a contiguous, marked Date table to evaluate time context correctly.

9. Month-End Balance Calculation

Question:
Which DAX expression correctly returns the month-end balance?

A.

SUM(FactBalances[Balance])

B.

CALCULATE(
    SUM(FactBalances[Balance]),
    ENDOFMONTH('Date'[Date])
)

C.

AVERAGEX('Date', FactBalances[Balance])

D.

COUNT(FactBalances[Balance])

Correct Answer: B

Explanation:
ENDOFMONTH restricts the calculation to the last date of the month, which is required for month-end snapshot metrics.

10. Recognizing Semi-Additive Behavior

Question:
Which statement best describes a semi-additive measure?

A. It aggregates correctly across all dimensions
B. It should always be stored as a calculated column
C. It aggregates across some dimensions but not time
D. It cannot use CALCULATE

Correct Answer: C

Explanation:
Semi-additive measures aggregate normally across dimensions like product or region but require special logic when evaluated across time.

Final Exam Tips

• If a value represents a state, not an activity → think semi-additive
• Avoid SUM across dates for snapshot metrics
• Use CALCULATE with time functions
• Expect scenario-based questions, not pure syntax questions

Go back to the PL-300 Exam Prep Hub main page

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Model the data (25–30%)
   --> Create model calculations by using DAX
      --> Create a measure by using Quick Measures

Below are 10 practice questions (with answers and explanations) for this topic of the exam.
There are also 2 practice tests for the PL-300 exam with 60 questions each (with answers) available on the hub.

Practice Questions

1. Purpose of Quick Measures

Question:
What is the primary purpose of using a quick measure in Power BI?

A. To create calculated columns without using DAX
B. To generate common DAX measure patterns using guided input
C. To improve model refresh performance
D. To replace the need for a Date table

Correct Answer:
B

Explanation:
Quick measures provide prebuilt DAX templates that guide users through creating common calculations. They generate standard DAX measures that can be edited later. They do not eliminate the need for proper modeling or Date tables.

2. Nature of a Quick Measure

Question:
After creating a quick measure, how is it stored in the data model?

A. As a calculated column
B. As a hidden system calculation
C. As a standard DAX measure
D. As a Power Query transformation

Correct Answer:
C

Explanation:
Quick measures create regular DAX measures that appear in the Fields pane and behave exactly like manually written measures.

3. Editing Generated DAX

Question:
A user creates a quick measure for Year-to-Date Sales. Can the generated DAX be modified?

A. No, quick measures are locked
B. Only in the Model view
C. Yes, like any other DAX measure
D. Only by recreating the quick measure

Correct Answer:
C

Explanation:
Once created, a quick measure is fully editable and behaves like any other DAX measure.

4. Time Intelligence Dependency

Question:
A Year-over-Year quick measure returns incorrect results. What is the most likely cause?

A. The measure was created in the Data view
B. The Date table is not marked as a Date table
C. The visual uses too many filters
D. The measure needs to be a calculated column

Correct Answer:
B

Explanation:
Time intelligence quick measures rely on a proper Date table that is marked as such and related to the fact table. Without it, results may be incorrect.

5. Model Size Impact

Question:
What impact do quick measures have on the size of the data model?

A. They increase model size significantly
B. They add new hidden tables
C. They increase memory usage only at refresh time
D. They do not increase model size

Correct Answer:
D

Explanation:
Measures, including quick measures, are calculated at query time and do not store data, so they do not increase model size.

6. Running Total Behavior

Question:
Which DAX concept is most commonly used in a running total quick measure?

A. Row context
B. RELATED
C. CALCULATE with ALL or FILTER
D. LOOKUPVALUE

Correct Answer:
C

Explanation:
Running total quick measures typically use CALCULATE combined with FILTER and ALL to override filter context and accumulate values over time.

7. Appropriate Use Case

Question:
When is a quick measure most appropriate?

A. When implementing complex business logic
B. When optimizing memory-intensive models
C. When creating a standard calculation pattern quickly
D. When creating relationships between tables

Correct Answer:
C

Explanation:
Quick measures are ideal for standard, well-known calculation patterns such as YTD, running totals, and ratios—not for complex custom logic.

8. Common Mistake

Question:
Which mistake is commonly made when using quick measures?

A. Using them only in visuals
B. Forgetting they generate DAX that depends on filter context
C. Using them only in Power Query
D. Creating too many quick measures

Correct Answer:
B

Explanation:
Quick measures are still subject to filter context. Misunderstanding this can lead to incorrect results, especially in complex visuals.

9. Relationship Dependency

Question:
A quick measure calculates a ratio using two tables but returns blank values. What is the most likely issue?

A. The measure should be a calculated column
B. The tables lack a valid relationship
C. The data types are incorrect
D. The quick measure category is wrong

Correct Answer:
B

Explanation:
Quick measures rely on the existing data model relationships. If relationships are missing or incorrect, the measure may return blanks.

10. Exam Interpretation Question

Question:
On the PL-300 exam, a question references a “guided DAX calculation created through the user interface.” What is this most likely referring to?

A. Calculated tables
B. Power Query steps
C. Quick measures
D. Implicit measures

Correct Answer:
C

Explanation:
“Guided DAX calculation” is a common exam phrasing used to describe quick measures, which guide users through creating DAX measures.

Final Exam Tip

For PL-300:

• Expect scenario-based questions
• Focus on when to use quick measures—not how to click them
• Understand the DAX patterns they generate
• Know their dependencies and limitations

Go back to the PL-300 Exam Prep Hub main page

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Model the data (25–30%)
   --> Create model calculations by using DAX
      --> Create calculated tables or columns

Below are 10 practice questions (with answers and explanations) for this topic of the exam.
There are also 2 practice tests for the PL-300 exam with 60 questions each (with answers) available on the hub.

Practice Questions

Question 1

You need to create a column that classifies customers as “High Value” or “Standard” based on their lifetime sales. The value does not need to change based on report filters.

Which approach is MOST appropriate?

A. Create a measure
B. Create a calculated column
C. Create a calculated table
D. Use a visual-level filter

Correct Answer: B

Explanation:
The classification is row-level and static, making a calculated column the correct choice. Measures are dynamic and filter-dependent, which is unnecessary here.

Question 2

A calculation must change dynamically when slicers are applied. Which option should you use?

A. Calculated column
B. Calculated table
C. Measure
D. Power Query custom column

Correct Answer: C

Explanation:
Only measures respond to filter context. Calculated columns and tables are evaluated at refresh and do not change with slicers.

Question 3

You create a calculated column that references a measure. What happens?

A. The column updates dynamically
B. The column returns blank
C. Power BI throws an error
D. The measure is converted to row context

Correct Answer: C

Explanation:
Measures cannot be referenced directly inside calculated columns because measures require filter context, which is not available during column evaluation.

Question 4

Which scenario is BEST suited for a calculated table?

A. Creating a sales KPI
B. Creating a Date dimension
C. Calculating profit margin
D. Filtering a visual dynamically

Correct Answer: B

Explanation:
Calculated tables are commonly used to create Date tables, helper tables, and bridge tables. KPIs and margins should be measures.

Question 5

Which statement about calculated columns is TRUE?

A. They are evaluated at query time
B. They respond to slicers dynamically
C. They increase model size
D. They are not stored in memory

Correct Answer: C

Explanation:
Calculated columns are stored in the model, increasing memory usage. Measures are calculated at query time and not stored.

Question 6

You need a table that aggregates sales by product and category to support a relationship. What should you create?

A. Measure
B. Calculated column
C. Calculated table
D. Visual aggregation

Correct Answer: C

Explanation:
Aggregated datasets that need to participate in relationships should be created as calculated tables.

Question 7

Which DAX function is MOST commonly used when creating calculated tables?

A. CALCULATE
B. SUM
C. SUMMARIZE
D. DIVIDE

Correct Answer: C

Explanation:
SUMMARIZE is commonly used to group and aggregate data when creating calculated tables.

Question 8

Why should calculated columns be avoided for large datasets when possible?

A. They cannot be indexed
B. They slow down visuals
C. They increase memory consumption
D. They do not support relationships

Correct Answer: C

Explanation:
Calculated columns are stored in memory. Overusing them can significantly increase model size and degrade performance.

Question 9

Which task should generally be performed in Power Query instead of using a calculated column?

A. Creating a slicer field
B. Creating a sort-by column
C. Cleaning and transforming raw data
D. Creating relationship keys

Correct Answer: C

Explanation:
Power Query is optimized for data cleansing and transformation and should be preferred over calculated columns whenever possible.

Question 10

A calculated table is created using DAX. When is it evaluated?

A. Every time a slicer changes
B. Every time a visual loads
C. During data refresh
D. At report open

Correct Answer: C

Explanation:
Calculated tables (like calculated columns) are evaluated only during data refresh, not during report interaction.

Exam Takeaways

• ✔ Calculated columns → row-level, static logic
• ✔ Calculated tables → model support and structure
• ✔ Measures → dynamic, filter-aware calculations
• ❌ Avoid calculated columns for aggregations
• ❌ Avoid calculated tables for data cleaning

Go back to the PL-300 Exam Prep Hub main page

This post is a part of the PL-300: Microsoft Power BI Data Analyst Exam Prep Hub; and this topic falls under these sections:
Model the data (25–30%)
   --> Create model calculations by using DAX
      --> Create calculation groups

Below are 10 practice questions (with answers and explanations) for this topic of the exam.
There are also 2 practice tests for the PL-300 exam with 60 questions each (with answers) available on the hub.

Practice Questions

Question 1

What is the primary purpose of a calculation group?

A. To replace all measures in a model
B. To apply reusable calculation logic to multiple measures
C. To improve data refresh performance
D. To create row-level security rules

Correct Answer: B

Explanation:
Calculation groups allow a single calculation (such as YTD or YoY) to be reused across multiple measures using SELECTEDMEASURE().

Question 2

Which function is REQUIRED when defining a calculation item?

A. CALCULATE
B. VALUES
C. SELECTEDVALUE
D. SELECTEDMEASURE

Correct Answer: D

Explanation:
SELECTEDMEASURE() references the measure currently in context, allowing the calculation group to work dynamically across measures.

Question 3

Where are calculation groups created?

A. Power BI Desktop
B. Power Query Editor
C. Tabular Editor
D. DAX Studio

Correct Answer: C

Explanation:
Calculation groups are created using Tabular Editor, an external modeling tool. They cannot be created directly in Power BI Desktop.

Question 4

Which scenario is BEST suited for a calculation group?

A. Creating a one-time KPI
B. Creating a simple ratio measure
C. Applying YTD, MTD, and YoY logic across many measures
D. Cleaning source data

Correct Answer: C

Explanation:
Calculation groups excel when the same calculation logic must apply consistently across many measures.

Question 5

What happens if multiple calculation groups exist in a model?

A. Power BI randomly applies one
B. Only the most recent one is used
C. Calculation precedence determines the order of execution
D. All calculation groups are ignored

Correct Answer: C

Explanation:
Calculation groups are applied based on precedence. Higher precedence values are evaluated first.

Question 6

Which statement about calculation groups is TRUE?

A. They are evaluated during data refresh
B. They increase model storage size significantly
C. They modify measures at query time
D. They can replace the need for base measures

Correct Answer: C

Explanation:
Calculation groups operate at query time, modifying how measures are evaluated without storing additional data.

Question 7

Why might a calculation group cause unexpected results?

A. It automatically filters fact tables
B. It overrides measure logic due to precedence
C. It recalculates columns dynamically
D. It disables relationships

Correct Answer: B

Explanation:
Incorrect calculation precedence can cause calculation groups to override or interfere with other calculations.

Question 8

Which is a limitation of calculation groups?

A. They cannot be used with measures
B. They require Power Query
C. They are not supported for all DirectQuery sources
D. They cannot be used in visuals

Correct Answer: C

Explanation:
Some DirectQuery sources have limited or no support for calculation groups, making them unsuitable in those scenarios.

Question 9

When should calculation groups generally NOT be used?

A. Large enterprise models
B. Models with many similar measures
C. Simple reports with only a few measures
D. Time intelligence scenarios

Correct Answer: C

Explanation:
In simple models, calculation groups may add unnecessary complexity and reduce clarity for report authors and users.

Question 10

Which best practice aligns with PL-300 guidance?

A. Use calculation groups to replace all measures
B. Use calculation groups only when they improve maintainability
C. Always create calculation groups for time intelligence
D. Avoid documentation when using calculation groups

Correct Answer: B

Explanation:
The exam emphasizes judgment and maintainability. Calculation groups should be used when they meaningfully simplify and standardize the model.

Key Exam Takeaways

• ✔ Calculation groups apply reusable logic to measures
• ✔ SELECTEDMEASURE() is foundational
• ✔ Created using Tabular Editor
• ✔ Precedence matters
• ❌ Not always appropriate for simple models

Go back to the PL-300 Exam Prep Hub main page