---
title: "Data Quality Firewall"
slug: "data-quality-firewall"
description: "Dataddo's Data Quality Firewall monitors 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: 2024-03-05T14:49:08Z
published: 2024-03-05T14:49:08Z
---

> ## 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 Firewall

***Data Quality Firewall*** is a feature available for ***data flows*** delivering data to [data storage destinations](/docs/data-storages) (e.g. [BigQuery](/docs/google-bigquery), [Snowflake](/docs/snowflake), [Synapse](/docs/azure-synapse), or [Amazon S3](/docs/s3)).

Its primary function is to **ensure the accuracy and quality** of the data being transferred. By checking and validating data before it reaches its destination, **the firewall offers mechanisms to prevent corrupted or non-compliant data from entering your systems**. By intercepting such data, Dataddo can notably reduce the complexity and overhead otherwise required to maintain the desired data quality level.

![Core Concepts - Data Quality Firewall](https://cdn.document360.io/084ed225-3f99-4644-a2da-39ca0cd5ef45/Images/Documentation/Core%20Concepts%20-%20Data%20Quality%20Firewall.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. **Blocking and Non-blocking Mode**: Select which operational mode ***Data Firewall*** should take in case of an issue.
  1. **Blocking Mode**: Stops the data transfer if it doesn't meet the established column-specific business rules. This ensures that downstream systems only receive compliant data.
  2. **Non-blocking Mode**: Allows the data to proceed even if issues are detected, logs the discrepancies for review, and sends a notification to the user.

## Configure Data Quality Firewall

1. In the **Flows** tab, click on your ***data 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. For next action steps, select **Block** to temporarily halt the entire data extraction process until you decide how to proceed.
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)

## Overriding Data Quality Firewall

Once you have set your rules up, they will be enforced even during a [manual data insert](/docs/data-backfilling). This might be undesirable as it can cause the historical data load to stop altogether

When manually inserting your data, you can opt for ignoring the rules by checking the **Skip flow rules validation** box.

![Data Quality - Skip rules](https://cdn.document360.io/084ed225-3f99-4644-a2da-39ca0cd5ef45/Images/Documentation/Data%20Quality%20-%20Skip%20rules.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.