Enterprise Data Masking Across Connected Systems
Protect sensitive implementation and test data wherever it travels. DataVault discovers sensitive data, applies reusable protection policies, traces it across connected systems and verifies whether protected data remains protected downstream.
Designed for connected enterprise landscapes including Workday, Oracle, SAP, Salesforce, databases, integration platforms and analytics systems.
Sensitive Data Doesn't Stop at the Source System
Enterprise implementation and test data frequently moves through ERP and HCM applications, CRM systems, integration platforms, databases, data lakes, reporting systems, extracts and files, and other downstream applications. Masking the source environment alone doesn't necessarily demonstrate that downstream copies are protected.
DataVault is designed to provide visibility into both source masking and downstream masking assurance.
One Data Protection Lifecycle Across Connected Systems
Discover → Classify → Protect → Trace → Verify → Monitor → Govern
Identify sensitive fields and records across connected application objects and data stores.
- Personal & contact information
- National & tax identifiers
- Bank & payroll details
- Supplier & customer information
Apply classifications such as PII, Financial, Contact, Payroll, Confidential, or customer-defined categories.
Apply policy types where implemented: redaction, partial masking, hashing, shuffling, substitution, synthetic replacement, tokenization.
Understand where sensitive data originates and where it moves.
Scan connected target systems to determine whether the required protection remains effective downstream.
Identify masking drift, newly exposed values, new sensitive fields, policy gaps and unverified downstream systems.
Provide policy visibility, masking status, coverage, exceptions, evidence and exportable reports.
Explore DataVault Capabilities
Each capability below goes deeper into one part of the DataVault lifecycle.
Data Masking →
Protect sensitive implementation and test data with reusable masking policies.
Downstream Masking →
Verify that masked data stays protected after it leaves the source system.
Test Data Management →
Discover, organize, protect and reuse valid data for enterprise testing.
Data Lineage →
Trace sensitive data from its source across connected enterprise systems.
Know What's Protected — and What Isn't
A representative view of the coverage dashboard shown to customers during onboarding and ongoing monitoring.
| Object | Sensitive | Masked | Exposed | Coverage |
|---|---|---|---|---|
| Workers | 1,104 | 1,021 | 83 | 92% |
| Suppliers | 8,220 | 8,180 | 40 | 99% |
| Customers | 14,442 | 13,920 | 522 | 96% |
| Bank Accounts | 2,310 | 2,310 | 0 | 100% |
Illustrative representative interface data, not a live customer environment.
Define Reusable Data Protection Policies
Policies are reusable across environments and, where mappings and connectors support it, across connected systems.
| Policy | Object / Field | Method | Classification |
|---|---|---|---|
| Supplier Email | email_address | Email Mask | PII |
| Bank Account | account_number | Partial Mask | Financial |
| National ID | national_id | Redact | PII |
| Tax Registration | tax_registration_no | Hash | Confidential |
Verify Protection Beyond the Source Application
Policy Applied
A masking or protection policy has been configured or executed.
Downstream Verified
DataVault has checked the relevant downstream target and confirmed the expected protection condition.
Drift Detected
DataVault has identified values or fields that no longer satisfy the expected protection policy.
Propagating a policy to a system is not the same as proving that system's data is protected — DataVault is designed to distinguish the two.
One View Across the Enterprise Data Landscape
DataVault is designed around a connector-based architecture for enterprise applications and data platforms. Coverage below reflects system categories the architecture targets — only explicitly validated connectors are represented as currently supported on a given customer's system pages.
Enterprise Applications
Data Platforms
Integration
Reporting / Analytics
Follow Sensitive Data From Source to Destination
Example Drill-Down
- Data Concept
- Employee Email
- Classification
- PII / Contact
- Source
- HCM Worker
- Policy
- Synthetic / Email Mask
- Downstream Verification
- CRM — Verified
- Data Lake — Drift detected
Keep Test Data Private Without Breaking Business Relationships
Independent random masking per system can make end-to-end testing unusable — if a supplier's name is masked one way in one system and a different way in another, cross-system test flows break. Deterministic masking strategies can preserve cross-system relationships while replacing sensitive source values, where configured and supported by the relevant connectors.
Source
Jane Smith
jane.smith@company.com
DataVault Masked Identity
Sarah Williams
sarah.williams@masked.test
| HCM | Sarah Williams |
| CRM | Sarah Williams |
| Data Lake | Sarah Williams |
| Reporting | Sarah Williams |
Deterministic masking strategies can preserve cross-system relationships where configured; universal referential consistency across every connector is not guaranteed and depends on the mappings implemented for a given landscape.
Detect When Protected Data Becomes Exposed Again
Masking Drift Detected
- System
- Data Lake
- Object
- Worker Extract
- Field
- personal_email
- Records affected
- 62
- Expected policy
- EMAIL_MASK
- Status
- Exposed
Illustrative interface example.
Protect Data After Environment Refreshes
DataVault can be incorporated into environment-refresh and test-data workflows. Automatic detection of refresh events depends on the integration configured for a given environment.
Know Whether an Environment Is Ready for Testing
DataVault Verified
Mandatory masking policies satisfied.
Attention Required
Sensitive records remain exposed or downstream verification is incomplete.
More Than Data Masking
DataVault can maintain reusable application-aware test data for automated testing — test-data discovery, object relationships, valid data selection, reusable test datasets, test dimensions, data refresh, masking, scenario-specific data, and Jarvis integration.
From Protected Data to Autonomous Testing
DataVault can have value independently of Jarvis and test execution — the two layer on top of the same protected data foundation.
DataVault
Discover · Protect · Organize · Verify
Jarvis
Understand · Generate · Expand Coverage
SyntraFlow
Execute · Schedule · Validate · Evidence
Built for Heterogeneous Enterprise Landscapes
Workday
HCM, worker and implementation/test-data scenarios.
Explore Workday DataVaultOracle Fusion
ERP, HCM and SCM application data.
Explore Oracle Data VaultSAP
Enterprise application and business-object data. Connector not yet validated.
Salesforce
CRM, customer and contact data. Connector not yet validated.
Data & Integration Platforms
Databases, data lakes, integration and reporting destinations.
Produce Evidence of Masking Coverage
Data Masking & Downstream Verification Report
Representative report contents: systems scanned, objects scanned, sensitive records, masked records, exposed records, source coverage, downstream coverage, masking policies, drift, verification status, and exceptions.
See a Sample ReportCommon DataVault Use Cases
Non-Production Data Protection
Protect sensitive information copied into implementation, test, UAT and development environments.
Downstream Masking Assurance
Verify that protection remains effective after data moves into connected systems.
ERP / HCM Implementation Testing
Use realistic but protected data during enterprise application implementation and regression testing.
Environment Refresh
Reapply and verify masking policies following test-environment refreshes.
Cross-System Testing
Maintain usable data relationships across integrated applications.
Test Data Management
Provide valid, reusable data to automated business-process tests.
Frequently Asked Questions
What is Syntra DataVault?
Is DataVault only for Oracle Fusion?
Can DataVault work with Workday?
Can DataVault verify downstream systems?
Does masking preserve test-data relationships?
Does DataVault make us GDPR compliant?
Can DataVault be used without SyntraFlow testing?
See How Your Data Stays Protected Across Connected Systems
Bring a representative source-to-downstream data flow to the demo. We'll show how DataVault can model sensitive data, protection policies, lineage, masking coverage and downstream verification for your enterprise landscape.