Reducing model size in Power BI - Cell-by-Cell Formula Trace

Sample Data

Sample product data with IDs, names, categories, and prices. This data is used to demonstrate reducing model size by removing unnecessary columns and filtering.

Cell	Value
A1	ProductID
B1	ProductName
C1	Category
D1	Price
A2	101
B2	Chair
C2	Furniture
D2	50
A3	102
B3	Table
C3	Furniture
D3	150
A4	103
B4	Pen
C4	Stationery
D4	2
A5	104
B5	Notebook
C5	Stationery
D5	5

Formula Trace

SUMX(FILTER(Products, Products[Category] = "Furniture"), Products[Price])

Step 1: FILTER(Products, Products[Category] = "Furniture")

Step 2: SUMX(filtered_table, filtered_table[Price])

Step 3: 200

Cell Reference Map

   A       B           C           D
1 ProductID ProductName Category    Price
2 101       Chair       Furniture   50
3 102       Table       Furniture   150
4 103       Pen         Stationery  2
5 104       Notebook    Stationery  5

Arrows point from Category and Price columns to the FILTER and SUMX functions.

The formula uses the Category column to filter rows and the Price column to sum values.

Result

   E
1 TotalFurniturePrice
2 200

The result shows the total price of products in the Furniture category, which is 200.

Sheet Trace Quiz - 3 Questions

What does the FILTER function do in this formula?

A Removes the Price column

B Keeps only rows where Category is Furniture

C Adds all prices together

D Changes product names

Key Result

FILTER narrows rows by condition; SUMX sums values over filtered rows.

Practice

1. Which of the following is a simple way to reduce the size of a Power BI data model?

easy

A. Import duplicate tables for safety

B. Add more calculated columns

C. Remove columns that are not used in reports

D. Enable auto date/time for all tables

Solution

1. Step 1: Identify unused data

   Unused columns take up space without adding value to reports.

2. Step 2: Remove unused columns

   Deleting these columns reduces the data model size and improves performance.

3. Final Answer:

   Remove columns that are not used in reports -> Option C

4. Quick Check:

   Removing unused data reduces model size [OK]

Hint: Delete unused columns to shrink model size quickly [OK]

Common Mistakes:

• Keeping all columns regardless of usage
• Adding calculated columns unnecessarily
• Enabling auto date/time increases model size

2. Which syntax correctly disables the auto date/time feature in Power BI using the Options menu?

easy

A. Go to File > Options > Data Load > uncheck 'Auto Date/Time'

B. Use DAX: DISABLE AUTODATE()

C. Right-click table > Disable Auto Date

D. In Power Query, remove date columns

Solution

1. Step 1: Locate auto date/time setting

   It is found under File > Options > Data Load in Power BI Desktop.

2. Step 2: Disable the feature

   Uncheck the 'Auto Date/Time' option to stop Power BI from creating hidden date tables.

3. Final Answer:

   Go to File > Options > Data Load > uncheck 'Auto Date/Time' -> Option A

4. Quick Check:

   Disabling auto date/time reduces hidden data [OK]

Hint: Disable auto date/time in Options to reduce hidden tables [OK]

Common Mistakes:

• Trying to disable auto date/time with DAX
• Removing date columns instead of disabling feature
• Looking for option in Power Query instead of Options menu

3. Given a table with a column 'SalesAmount' stored as Decimal Number, which change reduces model size the most without losing data precision?

medium

A. Keep 'SalesAmount' as Decimal Number

B. Change 'SalesAmount' data type to Whole Number

C. Change 'SalesAmount' data type to Text

D. Change 'SalesAmount' data type to Fixed Decimal Number

Solution

1. Step 1: Understand data types and size

   Decimal Number uses more space; Fixed Decimal Number stores decimals efficiently.

2. Step 2: Choose Fixed Decimal Number

   This type reduces size while keeping decimal precision, unlike Whole Number or Text.

3. Final Answer:

   Change 'SalesAmount' data type to Fixed Decimal Number -> Option D

4. Quick Check:

   Fixed Decimal Number reduces size with decimals [OK]

Hint: Use Fixed Decimal Number for decimals to save space [OK]

Common Mistakes:

• Switching to Whole Number loses decimal data
• Using Text increases model size
• Keeping Decimal Number wastes space

4. You notice your Power BI model size is large. You disabled auto date/time but the size did not reduce. What is the likely cause?

medium

A. You need to refresh the data after disabling auto date/time

B. There are many unused columns still in the model

C. Auto date/time disables only for new reports, not existing ones

D. The model size never changes after disabling features

Solution

1. Step 1: Check for unused columns

   Unused columns consume space even if auto date/time is off.

2. Step 2: Remove unused columns

   Deleting these columns will reduce model size effectively.

3. Final Answer:

   There are many unused columns still in the model -> Option B

4. Quick Check:

   Unused columns keep model large despite disabling features [OK]

Hint: Remove unused columns if disabling features doesn't reduce size [OK]

Common Mistakes:

• Assuming refresh fixes size without removing data
• Thinking auto date/time disables only for new reports
• Believing model size never changes

5. You have a large sales dataset with many columns, including detailed customer info not used in reports. You want to reduce model size and improve report speed. Which combination of actions is best?

hard

A. Remove unused customer columns, disable auto date/time, and change numeric columns to appropriate data types

B. Keep all columns, enable auto date/time, and add calculated columns for analysis

C. Remove only unused columns, keep auto date/time enabled, and leave data types as is

D. Disable auto date/time only, keep all columns and data types unchanged

Solution

1. Step 1: Remove unused columns

   Deleting unused customer info reduces unnecessary data in the model.

2. Step 2: Disable auto date/time

   This stops Power BI from adding hidden date tables that increase size.

3. Step 3: Optimize numeric data types

   Changing numeric columns to smaller or fixed decimal types saves space without losing precision.

4. Final Answer:

   Remove unused customer columns, disable auto date/time, and change numeric columns to appropriate data types -> Option A

5. Quick Check:

   Combining removal, disabling, and data type optimization reduces size best [OK]

Hint: Combine removing unused data, disabling features, and data type tuning [OK]

Common Mistakes:

• Keeping all data and enabling auto date/time
• Only removing columns without disabling features
• Ignoring data type optimization