🚧Impact Analysis
Overview
The Impact Analysis feature helps you understand the potential consequences of modifying or removing a resource within your data environment. Rather than providing a definitive audit of what will break, this tool is designed to answer the question:
“What might be affected if I change or remove this resource?”
This distinction is crucial. In the case of removing a specific field, the tool shows the exact resources that will break. For most other changes, it identifies everything that might be impacted—helping you make more informed and cautious decisions.
Triggering an Impact Analysis
To initiate an Impact Analysis:
Navigate to the Resource Side Panel of any supported resource.
Click the hamburger icon (☰) to display the dropdown list of available actions.
Select "Impact Analysis" to generate the report.
What Happens When an Impact Analysis is Triggered
For Fields
The system uses the following EQL query to identify downstream dependencies: has_upstream_fields(uri="<uri>"). This returns a list of all potentially affected downstream resources.
For Non-Field Resources (e.g., Tables)
Non-field resources, such as tables, are higher-level entities that contain multiple child fields. To properly assess the ripple effects of changes to these resources:
The system will:
Enumerate all child fields (columns) within the table.
Execute
has_upstream_fields(uri="<uri>")for each field individually.Aggregate and deduplicate the downstream results from all fields.
This ensures the analysis captures the complete downstream impact if the table is modified or removed.
Impact Analysis Report
The report consists of two primary sections:
Impacted Resources – Resources that will be affected if the root resource is changed or removed.
Impacted Users – Downstream users who may be affected (e.g., "David Smith," who created a dashboard that uses the impacted field).
Impacted Resources
After running the query, you’ll see an aggregated summary such as:
"Changing this resource will affect:" • 26 Dashboards • 783 Views • 32 Data Sources • 32 Snowflake Views • 12 dbt Models • 6 Tables
This provides a high-level snapshot of what may be at risk.
Exploring the Results
A search bar allows you to filter results by name.
Resources are grouped by type, and each group can be expanded to reveal details:
Click a category (e.g., “dbt Models” or “Dashboards”) to see specific impacted items.
For fields, the report shows their parent resource (e.g., a dbt model, table, or data source).
Expand each parent to view the exact fields that are affected.
This layered structure allows you to drill down and understand exactly which components are vulnerable to the change.
Impacted Owners
The second section of the report highlights who may be affected downstream:
This view identifies BI owners who might be impacted, based on usage metrics from the BI platform.
For each user, you will see summarized engagement data such as:
"732 impressions on 6 dashboards, 21 views, and 4 data sources"
This is determined by evaluating all resources in the critical downstream path of the changed resource.
Exploring the Results
The Impacted Owners View is organized into a clear, logical hierarchy, starting from the right-most (most downstream) resource and tracing back to the root resource:
Dashboard (123 impressions)
└── Field X in Data Source Y
├── Used in View 1
└── Used in View 2This structure helps you understand not only who is affected, but also how, from top-level dashboards down to the specific fields and views involved.
The list is sorted by impressions, ensuring that the most critical areas of impact appear first. The section is searchable by user name, allowing for quick identification of affected users. Each user entry includes a redirect icon that opens their context directly in the Data Model screen for deeper analysis.
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