Create calculated tables or columns (PL-300 Exam Prep)

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


Note that there are 10 practice questions (with answers and explanations) at the end of each topic. Also, there are 2 practice tests with 60 questions each available on the hub below all the exam topics.

Overview

Calculated columns and calculated tables are DAX-based modeling features used to extend and shape a Power BI data model beyond what is available directly from the source or Power Query. While both are created using DAX, they serve very different purposes and have important performance and modeling implications—a frequent focus area on the PL-300 exam.

A Power BI Data Analyst must understand when to use each, how they behave, and when not to use them.


Calculated Columns

What Is a Calculated Column?

A calculated column is a column added to an existing table using a DAX expression. It is evaluated row by row and stored in the model.

Full Name = Customer[First Name] & " " & Customer[Last Name]

Key Characteristics

  • Evaluated at data refresh
  • Uses row context
  • Stored in memory (increases model size)
  • Can be used in:
    • Relationships
    • Slicers
    • Rows/columns of visuals
    • Filtering and sorting

Common Use Cases for Calculated Columns

  • Creating business keys or flags
  • Categorizing or bucketing data
  • Creating relationship keys
  • Supporting slicers (e.g., Age Group)
  • Enabling sort-by-column logic

Example:

Age Group =
SWITCH(
    TRUE(),
    Customer[Age] < 18, "Under 18",
    Customer[Age] <= 65, "Adult",
    "Senior"
)


When NOT to Use a Calculated Column

  • For aggregations (use measures instead)
  • For values that change with filters
  • When the logic can be done in Power Query
  • When memory optimization is critical

PL-300 Tip: If the value depends on filter context, it should almost always be a measure, not a calculated column.


Calculated Tables

What Is a Calculated Table?

A calculated table is a new table created in the data model using a DAX expression.

Date Table =
CALENDAR (DATE(2020,1,1), DATE(2025,12,31))

Key Characteristics

  • Evaluated at data refresh
  • Stored in memory
  • Can participate in relationships
  • Acts like any other table in the model
  • Uses table expressions, not row context

Common Use Cases for Calculated Tables

  • Creating a Date table
  • Building helper or bridge tables
  • Pre-aggregated summary tables
  • Role-playing dimensions
  • What-if parameter tables

Example:

Sales Summary =
SUMMARIZE(
    Sales,
    Sales[ProductID],
    "Total Sales", SUM(Sales[SalesAmount])
)


Calculated Tables vs Power Query

AspectCalculated TablePower Query
EvaluationAt refreshAt refresh
LanguageDAXM
Best forModel logicData shaping
PerformanceCan impact memoryUsually more efficient
Source reuseModel-onlySource-level

Exam Insight: Prefer Power Query for heavy transformations and calculated tables for model-driven logic.


Key Differences: Calculated Columns vs Measures

FeatureCalculated ColumnMeasure
EvaluatedAt refreshAt query time
ContextRow contextFilter context
StoredYesNo
Used in slicersYesNo
Performance impactIncreases model sizeMinimal

Performance and Model Impact (Exam Favorite)

  • Calculated columns and tables increase model size
  • They are recalculated only on refresh
  • Overuse can negatively impact:
    • Memory consumption
    • Refresh times
  • Measures are preferred for:
    • Aggregations
    • Dynamic calculations
    • Large datasets

Common Exam Scenarios and Pitfalls

Common Mistakes (Often Tested)

  • Using calculated columns for totals or ratios
  • Creating calculated tables instead of Power Query transformations
  • Forgetting calculated columns do not respond to slicers dynamically
  • Building time intelligence in columns instead of measures

Best Practices for PL-300 Candidates

  • ✔ Use calculated columns for row-level logic and categorization
  • ✔ Use calculated tables for model support (Date tables, bridges)
  • ✔ Use measures for aggregations and KPIs
  • ✔ Prefer Power Query for data cleansing and reshaping
  • ❌ Avoid calculated columns when filter context is required

How This Appears on the PL-300 Exam

You may be asked to:

  • Choose between a calculated column, table, or measure
  • Identify performance implications
  • Determine why a calculation returns incorrect results
  • Select the correct modeling approach for a scenario

Expect scenario-based questions, not syntax memorization.


Final Takeaway

Understanding when and why to create calculated tables or columns—not just how—is critical for success on the PL-300 exam. The exam emphasizes modeling decisions, performance awareness, and proper DAX usage over raw formula writing.


Practice Questions

Go to the Practice Exam Questions for this topic.

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