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Data Check Rules

# Introduction

Data Check Rules allow administrators to identify records that do not comply with expected data quality criteria. Each rule specifies a target entity, a query to identify records of interest, and an optional condition for advanced validation logic.

When a rule is executed, it generates a set of log records representing failed validations. These logs can be reviewed, manually resolved, or serve as the basis for further automated actions.

Data Check Rule Form

# Entity Definitions

# Data Check Rule (talxis_datacheckrule)

Display Name Logical Name Description
Name talxis_name Name of the rule, typically includes its purpose or target field.
Entity Name talxis_entityname Logical name of the entity to which the rule applies.
Filter Query talxis_query FetchXML query identifying relevant records.
Condition (Function) talxis_conditionid Optional reference to a PowerFx-based function used for more advanced logic.
Description talxis_description Optional explanation of what the rule validates or checks.

# Data Check Log (talxis_datachecklog)

Display Name Logical Name Description
Data Record talxis_datarecordid Polymorphic lookup to the affected record.
Data Check Rule talxis_ruleid Reference to the rule that created this log.
Status (Reason) statuscode Current processing status (see table below).

# Status Values

Code Status Name Meaning
742070000 Evaluation Awaiting result of condition evaluation.
742070001 Pending Condition passed or not defined, needs user attention.
742070002 Checked Confirmed by user, optionally after manual correction.
742070003 Cancelled Condition evaluated to false.
742070004 Error Error occurred during evaluation.

# Rule Execution

Rules can be triggered in two ways:

# 1. Automatically

  • As part of a broader processing pipeline (e.g., after data import).
  • System filters rules by entity name and runs them on newly imported data.

⚠️ This applies only to Albert VAT App. See User Guide (opens new window) to get more info.

# 2. Manually

  • Rules can be run on demand from the admin UI.
  • The "Run Rule" button is available in the grid view of active rules.

Each rule execution creates one or more log entries in talxis_datachecklog, depending on the number of matching records.

# PowerFx Conditions

Rules may include an optional condition defined in a PowerFx-based Custom API (a Function). This enables scenarios that FetchXML cannot support, such as:

  • Calculations
  • Multi-entity logic
  • Value comparisons

# Requirements

  • Input: RecordId (string)
  • Output: Result (boolean)

Example function body:

{
  Result:
    LookUp('Invoice Lines','Line ID' = GUID(RecordId)).Amount > 1000
}
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If the condition returns true, a log entry is marked for review.

If false, the statuscode is set to cancelled.

# Manual Resolution

Users can resolve check logs via the following options:

  • Mark as Checked: Indicates that the data is acceptable despite the check failure.
  • Perform Correction: Launches a dialog to apply a correction directly to the source record. This creates a related Data Transformation Log.
  • ValidateCustomApiCondition – When a check rule includes a condition, this plugin executes the corresponding Function and updates the log status.

# Automation Integration

Data Check Rules can be used as part of larger workflows. Typical integration points include:

  • Post-import validation
  • Pre-submission data quality assurance
  • Audit trail creation

Each check log entry provides a clear indication of where data failed to meet defined criteria, enabling both reactive and preventive data governance.

Transformations