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Data Change Analysis

The Data points tab helps you understand whether the data inside objects has changed between the Baseline and Current versions.

This is especially useful after:

  • Script updates
  • Expression modifications
  • Data model changes
  • KPI logic adjustments

While the Sheet Layout tab evaluates structural differences, the Data Points tab focuses on actual data output changes.

Data Validation Scope

For each supported object, Regression performs a structured comparison of:

  • Number of rows
  • Number of cells
  • Data variance
  • Rows added
  • Rows deleted
  • Rows modified

This ensures that data changes are identified independently of layout updates.

Screenshot

Data Summary Metrics

Within the Summary sub-tab under Data Points, the following metrics are displayed:

  • Baseline row count
  • Current row count
  • Cell change count
  • Variance percentage
  • Rows added / deleted / modified

These metrics provide an immediate understanding of the extent of data changes.

Data Difference Analysis

When data differences are detected between versions, the following details are displayed:

  • variance percentage
  • Number of impacted rows
  • Highlighted cell-level changes

Based on the level of impact, these changes are categorized as:

  • Critical (high impact)
  • Warning (medium impact)

Newly Introduced Data

If an object contains no data in the Baseline version but includes data in the Current version:

  • Baseline row count = 0
  • Current row count > 0
  • All cells are marked as added
  • Status shown as Added

Review added data carefully to ensure it was expected.

Removed Data

If data exists in the Baseline version but is absent in the Current version:

  • Baseline row count > 0
  • Current row count = 0
  • All cells are marked as deleted
  • Status shown as Deleted

Data removal is considered a high-impact change and should be reviewed before deployment.

JSON Structural Comparison

In addition to numerical validation, the JSON Comparison sub-tab provides a structural comparison of object definitions. This enables deeper inspection beyond data-level changes.

Use Cases for JSON Analysis

JSON comparison is recommended when you need to:

  • Validate expression changes
  • Inspect property updates
  • Confirm structural modifications
  • Investigate unexpected behavior

This capability is particularly valuable for developers and QA teams.

JSON Comparison View

The comparison interface displays:

  • Baseline JSON on the left
  • Current JSON on the right

Differences are highlighted as follows:

  • Green - Added content
  • Red - Deleted content
  • Highlighted lines - Modified content

Screenshot

Common Structural Change Scenarios

Newly Created Object

  • No Baseline JSON
  • Entire structure appears as added

Deleted Object

  • No Current JSON
  • Entire structure appears as deleted

Modified Object

  • Specific lines show changes
  • Often reflects expression or property updates

Unsupported Object Types

Certain object types may not support regression data extraction.

In such cases, you may see messages such as:

  • Object type not supported for regression data extraction
  • Data comparison unavailable

If data comparison is unavailable:

  • Layout comparison may still work
  • JSON comparison may still be available depending on object type