> For the complete documentation index, see [llms.txt](https://help.daasity.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.daasity.com/core-concepts/dashboards/data-quality-and-validation.md).

# Data Quality & Validation

## Overview

Keeping your data accurate and reliable is essential for meaningful analysis. Daasity provides built-in tools and dashboards to help you validate and monitor your data quality across all integrations and reporting layers.

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### Account Health Dashboard

The Account Health Dashboard provides a high-level view of the overall state of your data pipelines. Use it to:

* Confirm that all integrations are syncing successfully.
* Review any failed or delayed extractions.
* Identify discrepancies in row counts or unexpected gaps in recent days.

This dashboard is the best place to check pipeline status at a glance, and should be part of your daily/weekly review routine.

### Onboarding Validation Dashboard

During onboarding, Daasity provides a Data Validation Dashboard that helps ensure all initial integrations are set up correctly. It surfaces checks such as:

* Order counts by day vs. your source system (UOS/UOS-based validation) .
* Sales vs. marketing spend totals aligning to external reports (UMS-based validation) .
* Retail POS feeds (URS) and syndicated market data (URMS) matching expected coverage  .
* Notification events (UNS) and traffic sessions (UTS) arriving in the expected ranges  .

These validations help you confirm that the unified schemas are producing correct outputs before you roll out dashboards to your teams.

### Ongoing Data Checks

Behind the scenes, Daasity’s Reporting Platform (drp) runs daily data validation tables that track duplicates, total execution time, and anomalies . These automated checks provide the foundation for what you see in dashboards and help proactively flag issues before they impact reporting.

{% hint style="info" %}
Tip: If you notice unusual results in any dashboard, use the Account Health Dashboard as your first stop. If the pipelines look healthy, move to source-specific validation dashboards to narrow down the issue.
{% endhint %}