About Automatically Fixing Consistency Check Errors

Use autofix to have Semantic Modeler automatically fix specific consistency check errors. Autofix helps you reduce the time you might spend manually correcting common modeling issues.

When consistency check finds an issue that you can correct automatically, Semantic Modeler identifies it in the consistency check results with the Autofix icon. You can click the icon to apply the required correction. See Automatically Fix a Consistency Check Error.

Semantic Modeler can automatically correct the following types of consistency check issues:

Analytic view dimensions without a default hierarchy: Semantic Modeler detects analytic view dimensions that don't specify a default hierarchy. If the dimension contains exactly one hierarchy, Semantic Modeler assigns that hierarchy as the default.
Data filters with an empty expression: Semantic Modeler detects data filters with null expressions or blank expression templates. Semantic Modeler assigns the expression 0 = 1. Semantic Modeler removes null data filter entries.
Data filters with an invalid or unknown expression data type: Semantic Modeler detects data filter expressions with invalid or unknown parsed data types. Semantic Modeler replaces the expression with 0 = 1.
Data filters with a nonconditional expression data type: Semantic Modeler detects data filter expressions whose parsed data types aren't Boolean. Semantic Modeler wraps the expression in a conditional comparison appropriate for its parsed data type.
Invalid complex join expressions: Semantic Modeler detects physical joins with complex join expressions that fail validation. Semantic Modeler removes the invalid physical join.
Invalid dynamic names: Semantic Modeler detects catalogs, schemas, and physical tables with invalid dynamic name values. Semantic Modeler clears the invalid dynamic name value.
Incorrect grand total settings in hierarchies: Semantic Modeler detects hierarchy levels that are incorrectly marked as grand total levels. Semantic Modeler removes the invalid grand total settings from non-root hierarchy levels.
Invalid logical joins: Semantic Modeler detects invalid logical joins between logical tables. Semantic Modeler removes the invalid logical join.
Logical columns with invalid physical mappings: Semantic Modeler detects physical mappings with missing source information, unavailable table mappings, missing physical expressions, references to nonexistent objects, references to unmapped physical tables, or expressions that fail physical expression validation. Semantic Modeler removes the invalid mappings.
Logical levels with circular preferred drill path entries: Semantic Modeler detects preferred drill path entries that create circular references. Semantic Modeler removes the related entry from the preferred drill path.
Logical levels with preferred drill path entries outside the business model: Semantic Modeler detects preferred drill path entries that reference objects outside the parent business model. Semantic Modeler removes the invalid entry from the preferred drill path.
Logical table sources with invalid data granularity entries: Semantic Modeler detects data granularity entries that aren't valid fully qualified logical level names. Semantic Modeler removes the invalid entries.
Logical table sources with invalid fragmentation content: Semantic Modeler detects data fragmentation expressions that fail parser validation in the fragmentation context. Semantic Modeler clears the invalid expression.
Presentation levels with an invalid or missing display column: Semantic Modeler detects presentation levels with missing or invalid display columns. Semantic Modeler assigns an existing presentation column that is sourced from the logical level's display, primary key, or additional key column. If no suitable presentation column exists, Semantic Modeler creates one and assigns it to the presentation level.
Presentation object aliases containing extra spaces: Semantic Modeler detects presentation object aliases with unintended leading or trailing spaces. Semantic Modeler removes the extra spaces from the alias value.
Presentation object names containing extra spaces: Semantic Modeler detects presentation objects that contain unintended leading or trailing spaces in their names. Semantic Modeler removes the extra spaces and automatically updates references to the renamed presentation object.
Presentation column names that don't match logical column names: Semantic Modeler detects presentation columns that are configured to use logical column names, but don't match the associated logical column names. Semantic Modeler updates the presentation column to match the connected logical column name.
Subject areas with invalid presentation table references: Semantic Modeler detects subject area table order entries that reference invalid presentation tables. Semantic Modeler removes the invalid entry from the table order.
Subject areas with no valid source business model: Semantic Modeler detects subject areas with no source business model or an incorrect source business model. Semantic Modeler determines a valid source business model from the presentation table order and updates the subject area.