The answer is that the data split column contains only NULL values, causing no rows to be assigned to the training set. This occurs because when you specify a custom column for `DATA_SPLIT_METHOD` in BigQuery ML, the service relies on non-NULL values in that column to partition your data into training and evaluation sets; if every value in that column is NULL, BigQuery ML cannot determine which rows belong to which set, so the training set receives zero rows and the model creation fails with an error about insufficient training data. On the Google Professional Machine Learning Engineer exam, this scenario tests your understanding of how BigQuery ML handles data partitioning, often appearing as a trap where candidates overlook that a column filled entirely with NULLs is functionally empty for splitting purposes. A common memory tip is to think of the split column as a gatekeeper: if every gate is NULL (meaning no gate exists), no data can pass through to the training set.
PMLE Architecting low-code ML solutions Practice Question
This PMLE practice question tests your understanding of architecting low-code ml solutions. The scenario asks you to isolate a root cause — eliminate options that address a different problem before choosing. After answering, compare your reasoning against the explanation and wrong-answer breakdown below. Once you have made your selection, read the full explanation to reinforce the concept and understand why each distractor is designed to mislead on exam day.
Exhibit
Refer to the exhibit.
```
CREATE OR REPLACE MODEL `mydataset.housing_model`
OPTIONS
(model_type='linear_reg',
input_label_cols=['price'],
data_split_method='custom',
data_split_col='split_flag')
AS
SELECT * FROM `mydataset.housing_data`
```
The table `housing_data` has 1000 rows. The `split_flag` column contains only NULL values. The model creation fails with the error: "Invalid state: The number of training data rows is 0."
What is the most likely cause of the error?
Clue words in this question
Noticing these words before you look at the options changes how you read each choice.
Clue: "most likely"
Why it matters: Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
Refer to the exhibit.
```
CREATE OR REPLACE MODEL `mydataset.housing_model`
OPTIONS
(model_type='linear_reg',
input_label_cols=['price'],
data_split_method='custom',
data_split_col='split_flag')
AS
SELECT * FROM `mydataset.housing_data`
```
The table `housing_data` has 1000 rows. The `split_flag` column contains only NULL values. The model creation fails with the error: "Invalid state: The number of training data rows is 0."
A
The data split column contains only NULL values, so no rows are assigned to the training set
Custom split requires non-NULL values 0,1,2.
B
The model type 'linear_reg' is incompatible with the column 'price' because of missing values
Why wrong: Missing values in price would cause a different error.
C
The model creation does not have permission to read the dataset in BigQuery
Why wrong: Would show an access denied error.
D
The model creation did not specify a training budget, so default is insufficient
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The data split column contains only NULL values, so no rows are assigned to the training set
Option A is correct because when the data split column contains only NULL values, BigQuery ML cannot assign any rows to the training set. The `DATA_SPLIT_METHOD` using a custom column requires non-NULL values in that column to partition data into training and evaluation sets; if all values are NULL, the training set receives zero rows, causing the model creation to fail with an error about insufficient training data.
Key principle: Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
✓
The data split column contains only NULL values, so no rows are assigned to the training set
Why this is correct
Custom split requires non-NULL values 0,1,2.
Clue confirmation
The clue word "most likely" in the question point toward this answer.
Related concept
Read the scenario before looking for a memorised answer.
✗
The model type 'linear_reg' is incompatible with the column 'price' because of missing values
Why it's wrong here
Missing values in price would cause a different error.
✗
The model creation does not have permission to read the dataset in BigQuery
Why it's wrong here
Would show an access denied error.
✗
The model creation did not specify a training budget, so default is insufficient
Why it's wrong here
Default budget is 1000, which is fine.
Common exam traps
Common exam trap: answer the scenario, not the keyword
Google Cloud often tests the subtle distinction between missing values in the label column (which are handled gracefully) versus missing values in the data split column (which can cause a complete failure), leading candidates to incorrectly blame missing values in the target column.
Trap categories for this question
Command / output trap
Would show an access denied error.
Detailed technical explanation
How to think about this question
In BigQuery ML, when using `DATA_SPLIT_METHOD = 'COLUMN'` with a specified split column, the query filters rows where that column is NULL to be excluded from training. If every row has NULL in that column, the training set becomes empty, and the model fails with an error like 'No training data found.' This is a common pitfall when the split column is not properly populated, especially after a JOIN or when the column is derived from an expression that yields NULL.
KKey Concepts to Remember
Read the scenario before looking for a memorised answer.
Find the constraint that changes the correct option.
Eliminate answers that are true in general but not in this case.
TExam Day Tips
→Watch for words such as best, first, most likely and least administrative effort.
→Review why wrong options are wrong, not only why the correct option is correct.
Key takeaway
Answer the scenario, not the keyword: identify the specific constraint before choosing the most familiar-sounding option.
Real-world example
How this comes up in practice
A company's IT admin needs to give a contractor read-only access to production logs without sharing account credentials. Using role-based access control (RBAC) and temporary scoped permissions — not a permanent shared password — is the correct pattern. Questions like this test whether you can apply least-privilege access across cloud identity services.
What to study next
Got this wrong? Here's your next step.
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Architecting low-code ML solutions — This question tests Architecting low-code ML solutions — Read the scenario before looking for a memorised answer..
What is the correct answer to this question?
The correct answer is: The data split column contains only NULL values, so no rows are assigned to the training set — Option A is correct because when the data split column contains only NULL values, BigQuery ML cannot assign any rows to the training set. The `DATA_SPLIT_METHOD` using a custom column requires non-NULL values in that column to partition data into training and evaluation sets; if all values are NULL, the training set receives zero rows, causing the model creation to fail with an error about insufficient training data.
What should I do if I get this PMLE question wrong?
Identify which exam domain this question belongs to, review the core concept, then practise similar questions from the same domain.
Are there clue words in this question I should notice?
Yes — watch for: "most likely". Probability qualifier — the question wants the most probable cause or outcome, not a guaranteed one. Eliminate low-probability options.
What is the key concept behind this question?
Read the scenario before looking for a memorised answer.
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Question Discussion
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