Configure Data Filter

Configure Data Filter

Data Filter controls which records continue through migration processing within a selected data type. Build each rule from known included and excluded examples, then verify the resulting record scope and the relationships that depend on it.

Data Filter changes record scope

Data selection chooses the supported data types included in the migration. Data Filter then determines which records inside a selected data type meet the configured field-based conditions.

Before you start

Prepare:

• the selected data type;
• the source field used for filtering;
• the supported operator;
• the comparison value;
• examples that should be included;
• examples that should be excluded;
• dependency checks for related data.

Filter controls

Each data-type filter can include:

Control	Purpose
Field	Selects the source field evaluated by the rule.
Operator	Defines how the source value is compared.
Value	Provides the comparison value.
Add Rule	Adds another condition to the same data-type filter.
Expression	Shows the combined filter expression generated from the configured rules.
Rule count	Shows how many rules apply to the data type.
Delete	Removes a rule or complete data-type filter where available.

Available fields and operators depend on the migration path and supported data model.

Configure a filter

1. Open Data Filter

   In Add-ons, expand Data Filter.

2. Select or locate the data type

   Use an existing data-type panel or add a filter for another selected data type where available.

3. Select the source field

   Choose the field that contains the value used to include or exclude records.

4. Select the operator

   Choose the operator that represents the required comparison.

5. Enter the comparison value

   Use the exact format expected by the source field.

6. Add more rules when needed

   Select Add Rule and configure each additional condition.

7. Review the generated expression

   Confirm that the expression represents the intended record scope.

8. Test representative records

   Check records that should match, should not match, and sit near the filter boundary.

Practical use cases

These examples show when Data Filter can solve a requirement by itself. Use only fields, operators, and values that are actually supported for the selected migration path.

Requirement	Data Filter role	What to verify
Start the Target Store with only active, saleable Products	Apply supported field-based conditions that include the approved active/in-stock Product population and exclude the rest.	Known included and excluded Products, filter-boundary records, and required Category, Review, Order, Manufacturer, or inventory relationships remain correct.
Migrate only Orders from an agreed business period or supported status	Apply a supported Order date or status condition without changing the selected Order fields or values.	Orders immediately inside and outside the boundary behave correctly and retained Orders remain linked to the required Customers and supporting records.

Review dependency risks

Filtering one data type can affect another.

Filtered data	Relationship risk
Products	Orders, Reviews, Categories, Manufacturers, and inventory references can point to excluded Products.
Customers	Orders can lose their Customer relationship.
Orders	Customer history and reporting can become incomplete.
Categories	Selected Products can lose the intended Category assignment.
Reviews	Review coverage can become incomplete for migrated Products.
Coupons	Historical Orders can reference excluded promotions.
CMS Pages or Blog Posts	Internal links, site mapping, or language coverage can become incomplete.

A valid expression can still produce an invalid business scope

Validate the filtered result as a connected dataset. Do not approve a filter solely because the expression is syntactically valid.

Interaction with later Add-ons

Data Filter is the first Add-on stage. Records that do not meet the filter should not be expected to receive later Advanced Data Mapping, Advanced Database Mapping, or Data Transformation processing.

When a later Add-on depends on a field used by a filter, confirm that the filter evaluates the intended source value and that the resulting record set is correct before reviewing mapping or transformation results.

Expected result

After configuring Data Filter:

• each rule targets the correct source field;
• the generated expression matches the approved scope;
• included and excluded examples behave as expected;
• dependent records remain usable or have an approved fallback;
• the resulting record set is ready for any applicable mapping and transformation stages.

Verify the filter

Check	Pass condition
Field	The rule evaluates the intended source field.
Operator	The operator represents the intended comparison.
Value	The comparison value uses the correct source format.
Expression	The generated expression matches the approved condition logic.
Boundary examples	Records at the inclusion and exclusion boundary behave correctly.
Relationships	Related data remains complete or has an approved fallback.
Entity Points	Newly included counted records fit the available Entity Points Plan.

If this does not work

Issue	What to do
A field is not available	Use another supported field only if it represents the same business requirement. Otherwise prepare the unsupported requirement for technical or Custom Service review.
The operator does not support the intended condition	Do not approximate the rule without approval. Request technical review.
The expression includes the wrong records	Correct the field, operator, value, or rule combination.
No records match	Check source values, formatting, capitalization, dates, and identifiers.
Relationships become incomplete	Broaden the filter or include the required related data.
The rule needs unsupported or bespoke logic	Document representative examples and expected results for Custom Service review.

Next step

Return to Configure Add-ons and review the filter before any applicable mapping or transformation rules.