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Microsoft PL-300 DAX Aggregations CALCULATE And Time Intelligence Practice Test

Skills 2.2 • 30 original questions

This Microsoft PL-300 Power BI Data Analyst practice test focuses on dax aggregations calculate and time intelligence through original scenario-based questions aligned to the skills measured as of April 20, 2026. Use the full ExamSnap PL-300 collection for broader practice across all current skill areas. For broader exam preparation, review the Microsoft PL-300 Exam Dumps page.

Instructions: Select the best answer for each question. Review the explanation after answering; each distractor includes a reason it is not the best choice for that scenario.

Question 1

During a regional reporting consolidation at Alpine Ski House, the analytics lead must define a reusable business aggregation that responds to report filter context. Which action most directly satisfies the requirement for the forecast report, analysis cycle 1?

Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Create a semi-additive measure that aggregates differently across time than across other dimensions
Build time-intelligence measures against a suitable date table
Create a DAX calculated table or calculated column when the result must be materialized during model refresh
Create a calculation group to apply reusable calculation items to existing explicit measures

Correct answer: A

Why: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. This directly addresses the stated requirement: define a reusable business aggregation that responds to report filter context.

Option review:

A: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. This directly addresses the stated requirement: define a reusable business aggregation that responds to report filter context.

B: Balances and snapshots often add across entities but require last-value, first-value, or another special rule across dates. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

C: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

D: Calculated tables and columns are stored model objects created from DAX and are appropriate when row-level or table-level results must persist. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

E: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

Learning point: Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX

Question 2

Wide World Importers is revising its analytics solution during a data-quality remediation. The team needs to modify the filter context used to evaluate a DAX expression. Which Power BI action should the BI developer choose for the mobile report, analysis cycle 1?

Build time-intelligence measures against a suitable date table
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required
Create a calculation group to apply reusable calculation items to existing explicit measures
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX
Use CALCULATE to evaluate an expression under modified filter context

Correct answer: E

Why: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. This directly addresses the stated requirement: modify the filter context used to evaluate a DAX expression.

Option review:

A: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

B: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

C: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

D: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

E: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. This directly addresses the stated requirement: modify the filter context used to evaluate a DAX expression.

Learning point: Use CALCULATE to evaluate an expression under modified filter context

Question 3

A design review for the executive report, analysis cycle 1 at Northwind Traders identifies one required capability: calculate period-based comparisons or accumulations using a proper date dimension. Which implementation is the strongest fit?

Create a semi-additive measure that aggregates differently across time than across other dimensions
Create a DAX calculated table or calculated column when the result must be materialized during model refresh
Build time-intelligence measures against a suitable date table
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX
Create a calculation group to apply reusable calculation items to existing explicit measures

Correct answer: C

Why: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. This directly addresses the stated requirement: calculate period-based comparisons or accumulations using a proper date dimension.

Option review:

A: Balances and snapshots often add across entities but require last-value, first-value, or another special rule across dates. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

B: Calculated tables and columns are stored model objects created from DAX and are appropriate when row-level or table-level results must persist. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

C: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. This directly addresses the stated requirement: calculate period-based comparisons or accumulations using a proper date dimension.

D: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

E: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

Learning point: Build time-intelligence measures against a suitable date table

Question 4

For the sales model, analysis cycle 2, Tailspin Toys wants the least indirect way to define a reusable business aggregation that responds to report filter context. Which Power BI feature or action should the self-service BI administrator select?

Create a calculation group to apply reusable calculation items to existing explicit measures
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required
Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Create a semi-additive measure that aggregates differently across time than across other dimensions
Create a DAX calculated table or calculated column when the result must be materialized during model refresh

Correct answer: C

Option review:

A: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

B: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

C: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. This directly addresses the stated requirement: define a reusable business aggregation that responds to report filter context.

D: Balances and snapshots often add across entities but require last-value, first-value, or another special rule across dates. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

E: Calculated tables and columns are stored model objects created from DAX and are appropriate when row-level or table-level results must persist. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

Learning point: Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX

Question 5

The data analyst at Alpine Ski House is comparing several approaches for a customer analytics initiative. The chosen approach must modify the filter context used to evaluate a DAX expression. Which option best meets that condition?

Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Use CALCULATE to evaluate an expression under modified filter context
Create a DAX calculated table or calculated column when the result must be materialized during model refresh
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX

Correct answer: B

Option review:

A: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

B: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. This directly addresses the stated requirement: modify the filter context used to evaluate a DAX expression.

C: Calculated tables and columns are stored model objects created from DAX and are appropriate when row-level or table-level results must persist. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

D: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

E: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

Learning point: Use CALCULATE to evaluate an expression under modified filter context

Question 6

A support escalation at Wide World Importers has been narrowed to one requirement: calculate period-based comparisons or accumulations using a proper date dimension. Which configuration should be investigated first for the operations dashboard, analysis cycle 2?

Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX
Build time-intelligence measures against a suitable date table
Use CALCULATE to evaluate an expression under modified filter context
Create a calculation group to apply reusable calculation items to existing explicit measures
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required

Correct answer: B

Option review:

A: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

B: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. This directly addresses the stated requirement: calculate period-based comparisons or accumulations using a proper date dimension.

C: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

D: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

E: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

Learning point: Build time-intelligence measures against a suitable date table

Question 7

An analytics governance review at Northwind Traders asks the analytics lead to define a reusable business aggregation that responds to report filter context. Which action aligns most directly with that requirement?

Build time-intelligence measures against a suitable date table
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required
Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Create a DAX calculated table or calculated column when the result must be materialized during model refresh

Correct answer: D

Option review:

A: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

B: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

C: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

D: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. This directly addresses the stated requirement: define a reusable business aggregation that responds to report filter context.

Learning point: Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX

Question 8

Before the regional workspace, analysis cycle 3 is released, the analytics team must modify the filter context used to evaluate a DAX expression. Which Power BI implementation should be added?

Create a semi-additive measure that aggregates differently across time than across other dimensions
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX
Build time-intelligence measures against a suitable date table
Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Use CALCULATE to evaluate an expression under modified filter context

Correct answer: E

Option review:

A: Balances and snapshots often add across entities but require last-value, first-value, or another special rule across dates. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

B: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

C: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

D: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

Learning point: Use CALCULATE to evaluate an expression under modified filter context

Question 9

Alpine Ski House is replacing a manual analytics process. The replacement must reliably calculate period-based comparisons or accumulations using a proper date dimension. Which choice should be implemented for the inventory model, analysis cycle 3?

Create a calculation group to apply reusable calculation items to existing explicit measures
Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Build time-intelligence measures against a suitable date table
Create a DAX calculated table or calculated column when the result must be materialized during model refresh
Create a semi-additive measure that aggregates differently across time than across other dimensions

Correct answer: C

Option review:

A: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

B: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

D: Calculated tables and columns are stored model objects created from DAX and are appropriate when row-level or table-level results must persist. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

E: Balances and snapshots often add across entities but require last-value, first-value, or another special rule across dates. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

Learning point: Build time-intelligence measures against a suitable date table

Question 10

Which Power BI action best matches this technical purpose for the service-level dashboard, analysis cycle 4: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations.

Create a DAX calculated table or calculated column when the result must be materialized during model refresh
Create a semi-additive measure that aggregates differently across time than across other dimensions
Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX
Use CALCULATE to evaluate an expression under modified filter context

Correct answer: C

Why: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. This directly addresses the stated requirement: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations..

Option review:

A: Calculated tables and columns are stored model objects created from DAX and are appropriate when row-level or table-level results must persist. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations..

B: Balances and snapshots often add across entities but require last-value, first-value, or another special rule across dates. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations..

C: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. This directly addresses the stated requirement: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations..

D: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations..

E: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations..

Learning point: Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX

Question 11

A runbook for the forecast report, analysis cycle 4 contains this description: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. Which Power BI feature or action belongs in the runbook?

Create a calculation group to apply reusable calculation items to existing explicit measures
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required
Create a DAX calculated table or calculated column when the result must be materialized during model refresh
Use CALCULATE to evaluate an expression under modified filter context
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX

Correct answer: D

Why: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. This directly addresses the stated requirement: CALCULATE changes the filter context for an expression and is central to many DAX business calculations..

Option review:

A: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: CALCULATE changes the filter context for an expression and is central to many DAX business calculations..

B: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: CALCULATE changes the filter context for an expression and is central to many DAX business calculations..

C: Calculated tables and columns are stored model objects created from DAX and are appropriate when row-level or table-level results must persist. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: CALCULATE changes the filter context for an expression and is central to many DAX business calculations..

D: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. This directly addresses the stated requirement: CALCULATE changes the filter context for an expression and is central to many DAX business calculations..

E: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: CALCULATE changes the filter context for an expression and is central to many DAX business calculations..

Learning point: Use CALCULATE to evaluate an expression under modified filter context

Question 12

During validation of the mobile report, analysis cycle 4, the report author needs a capability that behaves as follows: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. Which choice is correct?

Build time-intelligence measures against a suitable date table
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX
Create a calculation group to apply reusable calculation items to existing explicit measures
Use CALCULATE to evaluate an expression under modified filter context
Create a DAX calculated table or calculated column when the result must be materialized during model refresh

Correct answer: A

Why: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. This directly addresses the stated requirement: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows..

Option review:

A: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. This directly addresses the stated requirement: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows..

B: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows..

C: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows..

D: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows..

E: Calculated tables and columns are stored model objects created from DAX and are appropriate when row-level or table-level results must persist. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows..

Learning point: Build time-intelligence measures against a suitable date table

Question 13

A stakeholder asks why a particular Power BI feature should be used for the executive report, analysis cycle 5. The required behavior is: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. Which action provides that behavior?

Create a semi-additive measure that aggregates differently across time than across other dimensions
Create a calculation group to apply reusable calculation items to existing explicit measures
Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Create a DAX calculated table or calculated column when the result must be materialized during model refresh
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX

Correct answer: C

Why: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. This directly addresses the stated requirement: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations..

Option review:

A: Balances and snapshots often add across entities but require last-value, first-value, or another special rule across dates. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations..

B: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations..

C: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. This directly addresses the stated requirement: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations..

D: Calculated tables and columns are stored model objects created from DAX and are appropriate when row-level or table-level results must persist. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations..

E: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations..

Learning point: Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX

Question 14

The sales model, analysis cycle 5 is moving to production at Wide World Importers. Which action should be approved when the goal is to modify the filter context used to evaluate a DAX expression?

Build time-intelligence measures against a suitable date table
Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Create a calculation group to apply reusable calculation items to existing explicit measures
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX
Use CALCULATE to evaluate an expression under modified filter context

Correct answer: E

Option review:

B: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

Learning point: Use CALCULATE to evaluate an expression under modified filter context

Question 15

A data analyst at Northwind Traders must satisfy this acceptance criterion for the finance semantic model, analysis cycle 5: calculate period-based comparisons or accumulations using a proper date dimension. Which implementation is most appropriate?

Use CALCULATE to evaluate an expression under modified filter context
Create a calculation group to apply reusable calculation items to existing explicit measures
Build time-intelligence measures against a suitable date table
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX

Correct answer: C

Option review:

A: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

B: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

D: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

E: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

Learning point: Build time-intelligence measures against a suitable date table

Question 16

A operations scorecard redesign at Tailspin Toys can proceed only after the team can define a reusable business aggregation that responds to report filter context. What should the self-service BI administrator configure?

Build time-intelligence measures against a suitable date table
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required
Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Create a calculation group to apply reusable calculation items to existing explicit measures
Create a semi-additive measure that aggregates differently across time than across other dimensions

Correct answer: C

Option review:

A: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

B: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

D: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

E: Balances and snapshots often add across entities but require last-value, first-value, or another special rule across dates. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

Learning point: Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX

Question 17

The analytics team at Alpine Ski House has ruled out unrelated redesign work. Which action directly enables the team to modify the filter context used to evaluate a DAX expression for the customer report, analysis cycle 6?

Use CALCULATE to evaluate an expression under modified filter context
Create a semi-additive measure that aggregates differently across time than across other dimensions
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required
Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX

Correct answer: A

Option review:

A: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. This directly addresses the stated requirement: modify the filter context used to evaluate a DAX expression.

B: Balances and snapshots often add across entities but require last-value, first-value, or another special rule across dates. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

C: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

Learning point: Use CALCULATE to evaluate an expression under modified filter context

Question 18

An audit finding for the regional workspace, analysis cycle 6 says the current design cannot calculate period-based comparisons or accumulations using a proper date dimension. Which Power BI action most directly closes the gap?

Build time-intelligence measures against a suitable date table
Use CALCULATE to evaluate an expression under modified filter context
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX
Create a DAX calculated table or calculated column when the result must be materialized during model refresh

Correct answer: A

Option review:

A: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. This directly addresses the stated requirement: calculate period-based comparisons or accumulations using a proper date dimension.

B: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

C: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

D: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

E: Calculated tables and columns are stored model objects created from DAX and are appropriate when row-level or table-level results must persist. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

Learning point: Build time-intelligence measures against a suitable date table

Question 19

For the inventory model, analysis cycle 7, the analytics lead needs a repeatable solution that will define a reusable business aggregation that responds to report filter context. Which option should replace the current ad hoc process?

Use CALCULATE to evaluate an expression under modified filter context
Create a calculation group to apply reusable calculation items to existing explicit measures
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX
Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Create a semi-additive measure that aggregates differently across time than across other dimensions

Correct answer: D

Option review:

A: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

B: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

C: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

E: Balances and snapshots often add across entities but require last-value, first-value, or another special rule across dates. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

Learning point: Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX

Question 20

During a data-quality remediation, Tailspin Toys defines the desired outcome as follows: modify the filter context used to evaluate a DAX expression. Which Power BI capability should the team use?

Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX
Build time-intelligence measures against a suitable date table
Use CALCULATE to evaluate an expression under modified filter context
Create a calculation group to apply reusable calculation items to existing explicit measures
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required

Correct answer: C

Option review:

A: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

B: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

C: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. This directly addresses the stated requirement: modify the filter context used to evaluate a DAX expression.

D: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

E: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

Learning point: Use CALCULATE to evaluate an expression under modified filter context

Question 21

A new requirement is added to the forecast report, analysis cycle 7: calculate period-based comparisons or accumulations using a proper date dimension. Which action should the Power BI data analyst take?

Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX
Create a semi-additive measure that aggregates differently across time than across other dimensions
Create a DAX calculated table or calculated column when the result must be materialized during model refresh
Build time-intelligence measures against a suitable date table
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required

Correct answer: D

Option review:

B: Balances and snapshots often add across entities but require last-value, first-value, or another special rule across dates. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

C: Calculated tables and columns are stored model objects created from DAX and are appropriate when row-level or table-level results must persist. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

D: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. This directly addresses the stated requirement: calculate period-based comparisons or accumulations using a proper date dimension.

Learning point: Build time-intelligence measures against a suitable date table

Question 22

Wide World Importers is troubleshooting an unexpected reporting result. The decisive requirement is to define a reusable business aggregation that responds to report filter context. Which feature or configuration is most relevant?

Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required
Create a calculation group to apply reusable calculation items to existing explicit measures
Create a semi-additive measure that aggregates differently across time than across other dimensions
Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX

Correct answer: E

Option review:

A: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

B: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

C: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

E: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. This directly addresses the stated requirement: define a reusable business aggregation that responds to report filter context.

Learning point: Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX

Question 23

A technical workshop for the executive report, analysis cycle 8 documents this behavior: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. Which Power BI choice is being described?

Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX
Create a calculation group to apply reusable calculation items to existing explicit measures
Use CALCULATE to evaluate an expression under modified filter context
Create a semi-additive measure that aggregates differently across time than across other dimensions

Correct answer: D

Option review:

A: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: CALCULATE changes the filter context for an expression and is central to many DAX business calculations..

B: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: CALCULATE changes the filter context for an expression and is central to many DAX business calculations..

C: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: CALCULATE changes the filter context for an expression and is central to many DAX business calculations..

E: Balances and snapshots often add across entities but require last-value, first-value, or another special rule across dates. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: CALCULATE changes the filter context for an expression and is central to many DAX business calculations..

Learning point: Use CALCULATE to evaluate an expression under modified filter context

Question 24

The report author must identify the Power BI capability that provides this function: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. Which answer is correct for the sales model, analysis cycle 8?

Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required
Create a semi-additive measure that aggregates differently across time than across other dimensions
Build time-intelligence measures against a suitable date table
Create a calculation group to apply reusable calculation items to existing explicit measures
Create a DAX calculated table or calculated column when the result must be materialized during model refresh

Correct answer: C

Why: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. This directly addresses the stated requirement: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows..

Option review:

A: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows..

B: Balances and snapshots often add across entities but require last-value, first-value, or another special rule across dates. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows..

C: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. This directly addresses the stated requirement: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows..

D: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows..

E: Calculated tables and columns are stored model objects created from DAX and are appropriate when row-level or table-level results must persist. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows..

Learning point: Build time-intelligence measures against a suitable date table

Question 25

A modernization plan for the finance semantic model, analysis cycle 9 requires the team to define a reusable business aggregation that responds to report filter context. Which Power BI action is the clearest fit?

Create a semi-additive measure that aggregates differently across time than across other dimensions
Create a calculation group to apply reusable calculation items to existing explicit measures
Use CALCULATE to evaluate an expression under modified filter context
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required
Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX

Correct answer: E

Option review:

A: Balances and snapshots often add across entities but require last-value, first-value, or another special rule across dates. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

B: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

C: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

D: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

Learning point: Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX

Question 26

The analytics lead at Wide World Importers is creating a standard for the operations dashboard, analysis cycle 9. The standard must modify the filter context used to evaluate a DAX expression. Which feature should be documented?

Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Create a calculation group to apply reusable calculation items to existing explicit measures
Create a DAX calculated table or calculated column when the result must be materialized during model refresh
Use CALCULATE to evaluate an expression under modified filter context
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required

Correct answer: D

Option review:

B: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

D: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. This directly addresses the stated requirement: modify the filter context used to evaluate a DAX expression.

E: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: modify the filter context used to evaluate a DAX expression.

Learning point: Use CALCULATE to evaluate an expression under modified filter context

Question 27

Which implementation should Northwind Traders use for the customer report, analysis cycle 9 when the business requirement is to calculate period-based comparisons or accumulations using a proper date dimension?

Create a calculation group to apply reusable calculation items to existing explicit measures
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required
Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Create a DAX calculated table or calculated column when the result must be materialized during model refresh
Build time-intelligence measures against a suitable date table

Correct answer: E

Option review:

A: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

B: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

C: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

D: Calculated tables and columns are stored model objects created from DAX and are appropriate when row-level or table-level results must persist. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

E: Time-intelligence patterns compare or aggregate values across periods such as prior year, year to date, or rolling windows. This directly addresses the stated requirement: calculate period-based comparisons or accumulations using a proper date dimension.

Learning point: Build time-intelligence measures against a suitable date table

Question 28

A pilot review at Tailspin Toys finds that users still cannot define a reusable business aggregation that responds to report filter context. Which action should be completed before the regional workspace, analysis cycle 10 is expanded?

Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Create a calculation group to apply reusable calculation items to existing explicit measures
Create a semi-additive measure that aggregates differently across time than across other dimensions
Create a DAX calculated table or calculated column when the result must be materialized during model refresh
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX

Correct answer: A

Option review:

B: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

C: Balances and snapshots often add across entities but require last-value, first-value, or another special rule across dates. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

E: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: define a reusable business aggregation that responds to report filter context.

Learning point: Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX

Question 29

The data analyst needs to justify a Power BI design decision for the inventory model, analysis cycle 10. The feature must provide this behavior: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. Which selection is most defensible?

Create a DAX calculated table or calculated column when the result must be materialized during model refresh
Use CALCULATE to evaluate an expression under modified filter context
Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Create a calculation group to apply reusable calculation items to existing explicit measures
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required

Correct answer: B

Option review:

A: Calculated tables and columns are stored model objects created from DAX and are appropriate when row-level or table-level results must persist. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: CALCULATE changes the filter context for an expression and is central to many DAX business calculations..

B: CALCULATE changes the filter context for an expression and is central to many DAX business calculations. This directly addresses the stated requirement: CALCULATE changes the filter context for an expression and is central to many DAX business calculations..

C: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: CALCULATE changes the filter context for an expression and is central to many DAX business calculations..

D: Calculation groups reduce repetitive measures by applying DAX calculation items, such as time transformations, to selected measures. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: CALCULATE changes the filter context for an expression and is central to many DAX business calculations..

E: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: CALCULATE changes the filter context for an expression and is central to many DAX business calculations..

Learning point: Use CALCULATE to evaluate an expression under modified filter context

Question 30

For a semantic model modernization, the service-level dashboard, analysis cycle 10 must support the ability to calculate period-based comparisons or accumulations using a proper date dimension. Which option is technically aligned with that goal?

Create a DAX calculated table or calculated column when the result must be materialized during model refresh
Build time-intelligence measures against a suitable date table
Use basic statistical DAX functions to calculate values such as median, percentile, variance, or standard deviation when required
Create an explicit measure for a single aggregation such as SUM, COUNT, AVERAGE, MIN, or MAX
Use Quick measures to generate a supported calculation pattern and inspect or adapt the resulting DAX

Correct answer: B

Option review:

A: Calculated tables and columns are stored model objects created from DAX and are appropriate when row-level or table-level results must persist. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

C: DAX includes statistical functions that summarize distributions beyond simple totals and averages. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

D: Measures calculate at query time in the current filter context and are the normal way to define reusable business aggregations. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

E: Quick measures create DAX for common analytical patterns and can accelerate authoring when the built-in pattern matches the need. It is useful in another Power BI scenario, but it does not most directly satisfy this requirement: calculate period-based comparisons or accumulations using a proper date dimension.

Learning point: Build time-intelligence measures against a suitable date table

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