---
title: "Data Quality Watcher"
slug: "data-quality-watcher"
description: "Dataddo's Data Quality Watcher will check your data to avoid inaccuracies or errors caused by incomplete, corrupted data, or improperly formatted source data."
tags: ["Data quality", "Data flow", "How-to guide"]
updated: 2024-01-09T08:35:00Z
published: 2024-01-09T08:35:00Z
---

> ## Documentation Index
> Fetch the complete documentation index at: https://docs.dataddo.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Data Quality Watcher

**Data Quality Watcher** is a feature available for ***data flows*** with a [dashboarding app](/docs/dashboarding-apps) (e.g. [Looker Studio](/docs/looker-studio), [PowerBI](/docs/power-bi), or [Tableau](/docs/tableau)) as a ***data destination***.

It monitors the data to help prevent inaccuracies and errors, ensuring the quality and accuracy of the data being transferred. By scrutinizing and validating data before it reaches its intended destination, the ***Data Watcher*** provides mechanisms to alert you in case of discrepancies or issues. The data will be checked for **data anomalies**, **null**, or **zero** values that were caused by:

- Incomplete data,
- Corrupted data, and/or
- Improperly formatted source data.

![Core Concepts - Data Quality Watcher](https://cdn.document360.io/084ed225-3f99-4644-a2da-39ca0cd5ef45/Images/Documentation/Core%20Concepts%20-%20Data%20Quality%20Watcher.png)

## Key Features

1. **Data Checks**: Perform checks on null values, zero values, and anomalies. For more details on this process, refer to [the deep dive on data quality features](/docs/data-quality).
2. **Column-level Business Rules**: Configure and apply specific rules for each column. Column-level granularity allows for precise control, ensuring that only data meeting specific criteria is accepted for transfer.
3. **Email Notifications**: If the data don't meet the established column-specific business rules, the data transfer will proceed, but the user will receive an email notification detailing the error and the affected column..

## Configure Data Quality Watcher

1. In the **Flows** tab, click on your flow to edit it or [**create a new flow**](https://app.dataddo.com/flow/new).
2. Navigate to the **Data Quality Rules** tab and click on **Add Rule**.
3. Select for which columns you want to check null/zero/anomaly values.
4. Select **Email** notifications to be alerted whenever an error is found.
5. **Test** your rules before **Saving** the flow.

![Data Quality Watcher - Set up](https://cdn.document360.io/084ed225-3f99-4644-a2da-39ca0cd5ef45/Images/Documentation/Data%20Quality%20Watcher%20-%20Set%20up.png)

Data flows allow you to orchestrate the integration of your data from various sources to your desired destinations. You may add multiple data sources with the same schema to one flow to merge data for a consolidated output.

A destination is the endpoint where the data from your sources will be loaded. Destinations include dashboarding tools, data warehouses, and other online services.