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DQS Overview

Learn what Data Quality Sense is, how it works, and why Salesforce-native architecture matters for your data.

What is Data Quality Sense?

Data Quality Sense (DQS) is a Salesforce-native data profiling and quality analysis application. It helps you measure, understand, and improve your data quality to ensure reliable business decisions and AI-ready datasets.

DQS runs entirely within Salesforce. Your data never leaves the platform.

Key Differentiators

100% Salesforce-Native

DQS is built on the Salesforce platform using standard architecture:

ComponentTechnology
User InterfaceLightning Web Components (LWC)
ConfigurationCustom Metadata Types (CMT)
ProcessingApex Batch Jobs
StorageCustom Objects

Why native matters:

  • Your data stays in Salesforce (no export, no external APIs)
  • Uses existing Salesforce security and permissions
  • No integration to maintain or troubleshoot
  • Familiar interface for Salesforce users

No Code Required

Configure DQS through a point-and-click wizard. No Apex code, no formulas, no technical skills required.

The Definition Builder guides you through:

  1. Selecting what to measure
  2. Choosing which fields to analyze
  3. Setting thresholds and rules
  4. Reviewing and activating

Salesforce Admins can configure and run scans without developer support.

All Features Included

DQS is a single paid product. Every capability is available to all users:

  • All Data Quality dimension variants
  • AI Readiness (PII Detection)
  • Custom regex patterns
  • CSV export
  • Scheduling and recurring scans
  • Mentor Panel โ€” contextual, in-context recommendations based on what each scan just measured

The only usage limit is the per-org scan count (configurable, default 10 scans).

What DQS Measures

DQS organizes its capabilities into two dimensions:

Data Quality Dimension

Traditional data quality checks for operational hygiene:

CapabilityWhat It Measures
CompletenessAre required fields populated?
ValidityDo values match expected formats?
UniquenessAre records distinct?
TimelinessIs data current?
ConsistencyAre values uniform?

AI Readiness Dimension

Advanced check for Agentforce and AI preparation:

CapabilityWhat It Measures
PII DetectionIs sensitive data protected before AI exposure?

How DQS Works

The DQS Workflow

  1. Define what to analyze using the Definition Builder
  2. Configure thresholds and rules for each capability
  3. Execute scans that process your records in batches
  4. Review results with metrics and drill-down to affected records
  5. Act on findings โ€” guided by the Mentor Panelโ€™s contextual recommendations โ€” to improve data quality
  6. Monitor trends over time with recurring scans

Architecture Overview

โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚                     DEFINITION BUILDER                       โ”‚
โ”‚   Configure what to analyze, which fields, what thresholds  โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                              โ”‚
                              โ–ผ
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚                      SCAN EXECUTION                          โ”‚
โ”‚   Batch Apex processes records against selected capabilities โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                              โ”‚
                              โ–ผ
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚                      RESULTS STORAGE                         โ”‚
โ”‚   Metrics stored in custom objects for analysis and trends   โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜
                              โ”‚
                              โ–ผ
โ”Œโ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”
โ”‚                    RESULTS DASHBOARD                         โ”‚
โ”‚   View scores, drill down to records, export for cleanup     โ”‚
โ””โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”€โ”˜

Processing Model

DQS uses Salesforce Batch Apex for processing, which means:

  • Scalable: Handles millions of records
  • Governed: Respects Salesforce limits automatically
  • Background: Runs without blocking users
  • Resumable: Continues if interrupted

Processing cost varies by capability:

Cost LevelExample CapabilitiesNotes
LOWCompleteness, ValiditySimple field checks
MEDIUMTimeliness, Consistency, PII DetectionPattern analysis
HIGHUniquenessCross-record comparison

Key Concepts

Definition

A Definition is your configured data quality check. It specifies:

  • Which Salesforce object to analyze
  • Which fields to include
  • Which capabilities to run
  • What thresholds and rules to apply
  • What filters to narrow the scope

You can have multiple Definitions for different objects or use cases.

Capability

A capability is a specific type of data quality check (Completeness, Validity, etc.). Each capability has:

  • Variants: Different implementations of the same check
  • Metrics: What it measures (rates, counts, scores)
  • Configuration: Thresholds and options you set

Variant

A variant is a specific implementation of a capability. For example, Completeness has:

  • Global Fill Rate: Basic completeness percentage
  • Contextual Logic: Completeness with conditional rules

Metric

A metric is a specific measurement produced by a scan. Examples:

MetricTypeExample
Completeness RatePercentage85% of records have Email populated
Invalid CountInteger234 records have invalid email format
Dominant ValuesJSONTop 5 most common Industry values

Getting Started

Step 1: Install from AppExchange

  1. Go to Salesforce AppExchange
  2. Search for โ€œData Quality Senseโ€
  3. Click โ€œGet It Nowโ€ and follow the installation wizard
  4. Assign the DQS permission set to users

Step 2: Create Your First Definition

  1. Open DQS from the App Launcher
  2. Click โ€œNew Definitionโ€
  3. Follow the wizard to configure your first scan

For detailed guidance, see the Definition Builder Guide.

Step 3: Run and Review

  1. Save your Definition
  2. Click โ€œRun Scanโ€
  3. Wait for processing to complete
  4. Review your results

See Understanding Results for interpretation guidance.

Next Steps