---
title: "Data Quality Studio: Comining Data Quality with Lineage to Understand Impact"
url: "https://atlan.com/demos/data-quality-studio-comining-data-quality-with-lineage-to-understand-impact/"
description: "Trace data quality failures to affected assets and owners instantly! Take fast, informed action and keep data trust strong with Atlan’s Data Quality Studio."
format: "Video"
video: "https://videos.ctfassets.net/nwa1c00rtgxb/5e43var1Kbs2w1XDO2N7Wc/619fdfd4962abf470e9e02a99178defa/Combining_Data_Quality_with_Lineage_to_Understand_Impact.mp4"
content_purpose: ["Product Overview"]
target_persona: ["General", "Data Engineer", "Data Analyst", "Data Scientist", "Business User", "IT Administrator", "Data Steward", "Data Governance Lead"]
journey_stage: ["S2 - Discovery", "C1 - Onboarding", "C3 - Adoption", "C4 - Expansion"]
use_case_context: ["Training"]
product: ["Data Marketplace - Data Quality"]
content_type: "video transcript"
transcript_source: "contentful"
---

# Data Quality Studio: Comining Data Quality with Lineage to Understand Impact

Transcript of the video at https://atlan.com/demos/data-quality-studio-comining-data-quality-with-lineage-to-understand-impact/

<!-- Body: machine transcript stored on the Contentful entry (field contentBody), timestamps kept, product names corrected. Not yet edited by a person. -->

## Combining Data Quality with Lineage to Understand Impact

When a data quality issue occurs, understanding its impact and alerting the right people is crucial for reinforcing trust. Atlan’s Data Quality Studio can automatically send alerts through Slack or Teams for failures on Snowflake or Databricks, but the real power comes from its native lineage. With your full data estate connected, you can quickly trace downstream impact and immediately identify who needs to be informed and who to connect with for resolution.

Clicking on the asset icon on the left hand navigation takes us to the asset discovery page, showing us our cataloged data estate. In this case, we are looking to understand the impact of a recent data quality failure that we were alerted to, a null count failure on the Customer Dimension table for credit limit in Databricks. We click on the source filter and select our databricks connection. We then search for our customer dimension table and click on the name to bring the overview of the asset. We see that 4 rules have failed, aligning to our notification, so we click on the data quality tab to review. Here, we filter by the failed rules and can see that the credit limit column has failed, along with a few other columns.

While we are able to click on the lineage tab to get a graphical view of the table lineage generated automatically from Atlan’s workflows, expand the columns, seeing our credit limit column with a visual indication of the failure, and click on it to see the column level lineage automatically generated, giving us the impacted columns from the failure. Atlan’s data quality studio puts all the information right at the forefront. Going back to the data quality tab, on the right hand side there is the downstream impact section. Here, we immediately see that in total there are 4 columns that are failing, along with seeing that the table itself has 42 downstream assets. Clicking on the hyperlink brings up the impact report, which shows us all the metadata surrounding the downstream assets of the table, allowing us to initiate notifications of the impact. However, we can get even more granular from the data quality tab, ensuring that we alert the right users to the right column failures.

Expanding the unhealthy column listing shows all our columns, and we simply click on credit limit to see the exact column level impact report of the failure. Here, we see the metadata around the impacted assets and scrolling to the right, we see that Kaitleen is the owner, as she owns our BI assets. We can immediately notify her of the issues and impact to her assets via email, or, going back to the table, we could create a slack or teams message directly to her, alerting her of the issue and providing the context of the impacted assets.

With Atlan’s native lineage, you’re not just seeing where a data quality issue occurred—you’re seeing who it affects and how far it reaches. Paired with Atlan’s Data Quality Studio, you get immediate context on downstream impact, helping you keep data consumers informed and trust intact.