Issue: Not enough memory, unable to create simple table visual

1) Introduce proper dimension tables

You need a true star schema:

• One or more dimension tables (Date, Customer, Product, etc.)

• Each fact table connects only to dimensions

• No fact-to-fact relationships

Example:

DimCustomer ──▶ Fact_A DimCustomer ──▶ Fact_B DimCustomer ──▶ Fact_C

• Columns → from dimension tables

• Values → measures from facts

 Do NOT put fact columns directly into the table.

2) Use measures, not fact columns

Instead of this (problematic):

• Fact_A[Amount]

• Fact_B[Cost]

• Fact_C[Quantity]

Do this:

Amount A = SUM ( Fact_A[Amount] )
Cost B   = SUM ( Fact_B[Cost] )
Qty C    = SUM ( Fact_C[Quantity] )

• Rows → dimension attributes

• Values → these measures

This avoids row-level joins completely.

3) Check and fix relationship directions

Make sure:

• Single-direction filters from Dimension → Fact

• Avoid Both unless strictly required

• Avoid many-to-many unless unavoidable

Many-to-many + table visual = memory disaster.

Why you’re getting “There’s not enough memory”?

Even though you tried a star schema, this specific issue is caused by:

Reason-1: High-cardinality columns across multiple fact-like tables

Those 3 yellow tables look like:

• Large row counts

• Many text / ID / GUID columns

• Joined together in a single Table visual

Power BI tries to create a huge intermediate result set (VertiPaq explosion).

To FIX it, do these in order

1. NEVER put columns from 3 large tables in one table visual

Rule: A table visual should have 1 fact table + dimensions only

• Pick ONE of the yellow tables as the base
• Do not mix columns from all 3

2. Use DIMENSIONS only (no facts) for descriptive fields

• Move: Names, Status, Type, and Category into dimension tables
• Connect with 1-to-many, single direction

3. Replace columns with MEASURES

• This causes memory blow-up
• Raw numeric columns from multiple tables, use SUM(), COUNT(), DISTINCTCOUNT()
• Visual should be:
  • Dimension columns
  • Measures only

4. Reduce cardinality (VERY IMPORTANT)

In Power Query:

• Remove unused columns

• Remove GUID / long text if not required

• Turn off Auto Date/Time

• Prefer Integer keys over text

5. Check relationship direction

Set:

• Single direction

• Never bi-directional between large tables

Quick Architecture Rule (Remember this)

Table visual = multiple big tables

Table visual = dimensions + measures

If you still need data from all 3 tables, Create ONE consolidated fact table in Power Query:

• Merge once

• Load once

• Visual queries only one table

Remember:

• This is not a RAM issue
• This is a model + visual design issue
• Fix the visual grain + cardinality, memory error will disappear.

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Jaywant Thorat | MCT | Data Analytics Coach
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