Data Quality Monitoring

Keep your databases clean and trustworthy by automating the detection, alerting, and triage of data quality issues.

40 hrs
Time saved/month
6
Companies have mapped
Map This Automation

About This Automation

Data quality monitoring ensures incoming data meets standards before it reaches dashboards and reports. Manual validation is slow, error-prone, and delays detection of problems by hours or days.

Automation runs validation rules instantly on every data load, calculates quality scores, and alerts teams to issues in minutes. Bad data is caught before it reaches end users.

Key features
Execute validation rules automatically on every data load
Calculate data quality scores and identify failure patterns
Route alerts to the right team based on severity
Log all findings with metadata for audit and investigation
Refresh dashboards and reports when data is corrected

How The Automation Works

The full workflow, from trigger to completion.

1. Data Load Detectedtrigger

Automation is triggered when new data arrives in the staging database or a scheduled validation window opens. The trigger captures the dataset name, row count, and timestamp.

2. Run Validation Rules

The automation platform executes a suite of pre-configured validation rules against the dataset, checking for nulls, duplicates, out-of-range values, schema compliance, and referential integrity. Results are logged with severity levels.

3. Analyze Results and Score Quality

The automation evaluates validation results, calculates a data quality score, identifies patterns in failures, and determines if the issue is critical, warning, or informational.

4. Route Alert

If issues are found, a formatted alert is sent to the appropriate channel with the quality score, affected fields, record counts, and a link to the detailed report.

5. Log Issues to Tracking System

All detected issues are automatically logged to a centralized tracking system with metadata, severity, and timestamp, creating an audit trail and historical record.

6. Trigger Alert for Critical Issues

If data quality score falls below a critical threshold, an incident is automatically created to page the on-call engineer for immediate investigation.

7. Update Quality Dashboard

Validation results and quality metrics are pushed, updating a real-time data quality dashboard that shows trends, failure rates, and issue history.

4 reasons to map this process

1

It's completely free

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2

You get a complete build plan

A visual process map, automation spec, delivery timelines, and everything needed to build it, customized to your workflow and tools.

3

You see your real numbers

Custom pricing, ROI projection, and payback timeline based on your actual process, not industry averages.

4

There's no obligation to build

Your build plan stays in your workspace with no expiry. Move forward whenever the timing is right.

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Frequently asked questions

Everything you need to know before mapping this process.

This template is a starting point based on how other businesses handle this type of work. When you map your process, you describe exactly how your team does it and the automation is built around your workflow, not a generic template.

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Estimated Time Saving
40hrs/month
Process pain:8.2/10
Mapped by:6 Companies

Map this to your business to get your exact numbers.

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