Data validation in CI pipeline in MLOps - Step-by-Step Execution

Process Flow - Data validation in CI pipeline

Code Commit / Data Update

↓

Trigger CI Pipeline

↓

Run Data Validation Tests

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Continue Pipeline

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Deploy Model / Data

This flow shows how a data update triggers a CI pipeline that runs data validation tests. If tests pass, the pipeline continues; if they fail, it stops and alerts.

Execution Sample

MLOps

def validate_data(data):
    if data.isnull().sum().sum() > 0:
        return False
    if (data['age'] < 0).any():
        return False
    return True

result = validate_data(new_data)

This code checks if the data has missing values or negative ages and returns True if data is valid, False otherwise.

Process Table

Step	Check	Condition	Result	Action
1	Check missing values	data.isnull().sum().sum() > 0	False	Continue
2	Check negative ages	(data['age'] < 0).any()	True	Fail validation
3	Return validation result	N/A	False	Stop pipeline and alert

💡 Validation failed due to negative age values, pipeline stops to prevent bad data deployment.

Status Tracker

Variable	Start	After Step 1	After Step 2	Final
data.isnull().sum().sum()	N/A	0	0	0
(data['age'] < 0).any()	N/A	N/A	True	True
result	N/A	N/A	N/A	False

Key Moments - 2 Insights

Why does the pipeline stop even though there are no missing values?

Because the negative age check failed at step 2 (see execution_table row 2), which is critical for data quality, so the pipeline stops to prevent bad data deployment.

What happens if all checks pass?

If all checks pass (both conditions False), the validation returns True and the pipeline continues to deploy the model or data (not shown in this trace).

Visual Quiz - 3 Questions

Look at the execution table, what is the result of the missing values check at step 1?

A True

B None

C False

D Error

💡 Hint

Refer to execution_table row 1, column 'Result' shows False for missing values check.

At which step does the pipeline decide to stop?

A Step 3

B Step 1

C Step 2

D Pipeline never stops

💡 Hint

Look at execution_table row 3 where the validation result is False and action is to stop pipeline.

If the data had no negative ages, how would the 'result' variable change?

A It would be False

B It would be True

C It would be None

D It would cause an error

💡 Hint

Check variable_tracker for 'result' and consider if all conditions are False, validation returns True.

Concept Snapshot

Data validation in CI pipeline:
- Triggered by code or data update
- Runs checks like missing values and invalid data
- If validation passes, pipeline continues
- If validation fails, pipeline stops and alerts
- Prevents bad data/model deployment

Full Transcript

When new data or code is committed, the CI pipeline starts. It runs data validation tests step-by-step. First, it checks for missing values. If none are found, it checks for invalid data like negative ages. If any check fails, the pipeline stops and alerts the team to fix issues. If all checks pass, the pipeline continues to deploy the model or data safely. This process helps keep data quality high and prevents errors in production.