Why understanding data model matters for reporting?
Accurate reporting in Salesforce depends on understanding how data is stored and connected. Without this, you risk:
Choosing the wrong report type
Missing important objects or fields
Delivering misleading or incomplete insights
For example, a pipeline report broken down by product requires knowledge of how `Opportunities`, `OpportunityLineItems`, and `Products` relate. Missing the `OpportunityLineItem` means product-level data won’t be included at all.
A solid grasp of the schema ensures your reporting structure mirrors the actual data model, enabling reliable analytics, actionable dashboards, and stakeholder trust.
When to generate the data model diagram?
This approach is essential when:
Building or refining dashboards and reports
Designing custom report types
Troubleshooting broken or incomplete reports
Skip it only for very simple, standalone object reports where the schema is already well-known.
Prerequisites
Before you start, make sure:
Your Salesforce Org is connected to Elements.
You are a space editor.
You are a manager or editor on at least one of the connected Salesforce metadata dictionaries.
Data Model Generation is currently available in closed beta to the customers who have pre-registered for access.
We are planning GA release in May, subject to feedback from beta customers.
Perform data model analysis for accurate reporting
Step 1: Understand the reporting requirement
Start by clarifying the business question, not the data:
What’s the insight or decision the report supports?
What should be shown? (e.g., cases by product and region)
What is the level of detail (grain) needed? (e.g., one row per case or per asset?)
Example: “Provide a ‘Cases by Product & Region’ report that shows total case count and average resolution time aggregated at the product-region level.”
Step 2: Generate the data model from your Org
Use your business requirement, specifically the scope (e.g. 'Cases by Product & Region’ ) as an input into Data Model Generation.
Elements will use semantic analysis to propose a set of Salesforce objects. These are selected based on how closely their name and description match your query.
Additional related objects (via lookup or master-detail fields) are also identified to provide context. Select the scope as it surfaces the objects most likely involved in supporting the capability.
Step 3: Interpret and refine the diagram
Start analysis from your primary object, e.g., `Case` for customer support reporting Then follow relationships outward, i.e. look at lookup and master-detail relationships that connect to other objects. Identify related objects that contain needed data (e.g., `Asset`, `Product2`).
The generated data model diagram will only surface relationship fields relevant to the scope of selected objects. To find if those related objects contain data you are looking for, use the link to Object information on the card to navigate to metadata dictionary. From there you can review ALL fields available on the object.
Finally, assess relationship reliability. Just because there is a lookup/ master-detail relationship between two objects, it does not mean that it is useful for your report. Check following:
Are the relationship fields consistently populated?
Are there multiple paths to data?
Which one is cleanest?
Step 4: Map schema to custom report types
Now that you understand the existing schema and relationships:
Choose the correct primary object for your report type
Include related objects that were identified via the data model
Create or modify custom report types in Salesforce that reflect these relationships
If you identify missing or broken relationships (for instance when two objects are not related), raise user stories to address schema gaps.
