SAP Data Scrambling: 3 Common Misconceptions & The Secret to Success

SAP data scrambling is critical to protect business data. Over 90% of Fortune 500 companies manage their business operations using SAP systems. Each company typically maintains many non-production environments containing sensitive data. 

But when it comes to protecting SAP data, too many enterprise leaders believe the myths. 

To truly protect SAP data at your enterprise, you need to learn the truth and you need to adopt best practices. In this blog, we’ll share exactly that.

A Quick Primer on SAP and Data Privacy

What is SAP?

SAP is a comprehensive ERP (enterprise resource planning) platform. It helps organizations manage their business operations and information flows. Many global companies use SAP to store important and sensitive data. This data includes customer details, financial records, and employee information.

But this critical data comes with significant responsibility. Global organizations must comply with key regulations like the General Data Protection Regulation (GDPR), the California Consumer Privacy Act (CCPA), and the Health Insurance Portability and Accountability Act (HIPAA). Failure to do so risks noncompliance with standards like the Payment Card Industry Data Security Standard (PCI DSS) as well as costly penalties and reputational damage.

What is SAP Data Scrambling (and SAP Data Masking)?

Data scrambling is a technique that rearranges the characters or digits of a sensitive piece of data, like names or ID numbers. The result looks similar to the original data but is anonymized to protect private details. This scrambled data can then be used in testing or development systems. 

In most situations, data scrambling is a type of data masking. But in SAP, these two terms mean different things. To put it simply:

• SAP data scrambling refers to replacing sensitive information in stored data (data-at-rest) with anonymous, fictitious values.
• Data masking in SAP means hiding or obscuring sensitive values while it is being accessed at runtime. For example, a social security number may appear partially hidden like “XXX-XX-1234".

The SAP Data Scrambling Challenge

SAP Systems Requiring Protection

Most companies have copies of sensitive data throughout their SAP landscapes. The data does not only exist in the primary production system. There are also copies in testing (non-production) environments. These testing environments are where data scrambling is most needed.

The main parts of an SAP system that often contain sensitive data include:

• SAP ECC (the core business system)
• SAP S/4HANA (the newer version of ECC)
• SAP BW (the reporting system)
• SAP CRM (the customer management system)

According to the Perforce Delphix State of Data Compliance and Security Report, 54% of organizations have already experienced a data breach or theft involving sensitive data in non-production environments. A likely reason is that 86% of companies allow some data compliance exceptions in these environments. Alarmingly, this happens even though 91% of organizations express concern about the growing risk and expanded exposure footprint in non-production systems.

Technical Limitations of Native SAP Data Scrambling Solutions

Companies that only use SAP's built-in data scrambling features face several challenges. 

The protection options in standard SAP don't work well for all types of sensitive data. For example, they might mask credit card numbers but miss other identifying information. 

SAP environments also rarely operate in isolation; they integrate with non-SAP applications that must also be tested together. This integration testing requires consistent data scrambling across all systems to maintain referential integrity. 

Unfortunately, most native tools lack the capability to extend scrambling beyond SAP — leaving non-SAP apps exposed or inconsistently masked. This gap creates vulnerabilities and complicates compliance efforts.

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• Speed up your SAP development timelines while maintaining compliance with data privacy regulations.
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3 Common Myths about SAP Data Scrambling

"Manual Scrambling is Sufficient"

Many organizations still protect their data using manual processes. But this approach has serious drawbacks. 

For one, manual SAP data scrambling is slow and inconsistent, often taking weeks to complete.

It’s also prone to human error. Teams may struggle to identify and mask all instances of sensitive data consistently. Different team members might also handle different parts of the process, causing a range of protection qualities. 

Manual approaches can't keep up as data volumes grow and systems become more complex.

"Legacy Tools Meet Our Needs"

Some organizations may believe their existing tools are good enough for protecting data. But older tools often create problems with newer SAP systems. 

An example is SAP's own TDMS tool. It works with older ECC systems but does not support S/4HANA, SAP’s next-gen platform that organizations are beginning to migrate to.

The increased adoption of cloud environments has also caused problems with legacy tools. Many legacy tools don’t integrate well with cloud-native solutions. They also scale poorly across distributed cloud environments.

Most importantly, older tools can't preserve referential integrity across multiple systems and data sources. This makes it difficult to impossible to properly perform integration testing across an SAP implementation.

"We Don't Test with Sensitive Data"

The most dangerous misconception is thinking that test environments don't contain sensitive data. The reality is quite different. 

Most test SAP environments are filled with copies of personally identifiable information (PII). These copies include sensitive information like customer, employee, and financial data. Development and testing systems comprise about 80% of the places hackers could break in. These systems are less secure than production systems, increasing the risks of data breaches. Growing regulatory penalties make this approach increasingly risky. 

Industry Examples for SAP Data Scrambling

Here are examples of how real-world businesses can successfully use SAP data scrambling strategies.

Financial Services Example

A global financial institution may implement comprehensive data masking for their SAP landscape to:

• Secure customer financial data in development environments.
• Meet banking-specific regulations (GLBA, PCI DSS).
• Reduce compliance-related delays in their digital transformation initiatives.

Outcomes: The bank can reduce development cycle times by 40% while eliminating compliance-related project delays, accelerating their SAP S/4HANA migration timeline.

Healthcare Implementation Example

A leading healthcare provider may deploy automated data masking across their SAP landscape in order to:

• Protect patient data across clinical and administrative systems.
• Ensure HIPAA compliance in non-production environments.
• Support digital health innovations while safeguarding PHI.

Outcomes: The organization eliminates compliance findings related to test data, reduces data provisioning times from weeks to hours, and avoids HIPAA violations.

Retail Deployment Scenario

A multinational retailer may implement automated data masking to:

• Secure customer payment information while maintaining testing accuracy.
• Support omnichannel development with masked/protected customer profiles.
• Maintain compliance across global operations with varying privacy requirements.

Outcomes: The retailer could reduce time-to-market for new features by 60% while maintaining comprehensive privacy controls across their testing landscape.

5 Best Practices for SAP Data Scrambling

To improve SAP data scrambling, follow these key practices: 

1. Locate All Sensitive Data

First, create a complete inventory of sensitive data across all your SAP systems. You can't protect what you don't know about. Identifying where sensitive data exists is a crucial first step. This inventory should include personal, financial, and other regulated information.

2. Set Up Consistent Protection Rules

Next, you must establish consistent protection policies for all environments. Apply rules for protecting sensitive information the same way across systems. This consistency helps prevent protection gaps and simplifies compliance reporting. 

For example, with Perforce Delphix, you gain both an automated sensitive data discovery solution AND in-house SAP knowledge. We’ve worked with large enterprises on SAP implementations and helped them set up the consistent rules they need to protect SAP data.

3. Utilize Automation

Automate the refresh-and-mask process for your non-production environments. Protection should happen when you copy data for your test, sandbox, UAT, and pre-production systems. 

4. Integrate Workflows

Integration between masking and data provisioning workflows is also essential. The protection process should be built into the data delivery process across teams. 

5. Update Rules and Processes Regularly

Finally, maintain your protection rules through SAP upgrades and migrations. As your systems change, your data masking approach must also evolve. This means regularly reviewing and updating your masking rules to ensure continued compliance. 

Successful SAP data masking addresses both technical solutions and team processes. Having great tools isn't enough. You will also need clear responsibilities and workflows to ensure consistent protection.

Enterprise-Grade SAP Data Scrambling with Perforce Delphix

Perforce Delphix offers simple but powerful data scrambling designed for SAP systems. It protects data across both SAP and non-SAP applications. Get ahead of compliance blockers that could slow down your SAP projects.

Advanced Data Compliance Capabilities

Delphix replaces sensitive information with realistic but fake data. It does not simply replace values with random characters or zeros. Instead, it creates test data that works like production data without exposing actual information. 

The solution maintains data relationships that keep systems working. When a customer record gets scrambled, all connected orders, payments, and other details also get updated. This ensures that test systems function correctly with protected data.

Delphix helps enterprises like you comply with privacy laws by providing consistent, auditable data compliance. It preserves master data functionality so essential business processes can be adequately tested.

Fast, Compliant Data Delivery

With Delphix, teams can deliver scrambled data copies to testing teams in minutes instead of weeks. The automated approach eliminates manual steps that slow down projects. This can accelerate SAP projects by 50%.

Create virtual data copies that use far less storage space than traditional copies. These virtual copies can decrease your disk storage costs by 80%. This saves on infrastructure costs and lets you provide more test environments for development teams.

Refresh or rewind data as needed. Teams can quickly reset to a clean state if a test corrupts data or produces unexpected results. The space-efficient data approach lets you expand from N+1 to N+many landscapes to parallelize projects. This cuts down waiting time and reduces delays in testing.

Easy SAP Integration and Compliance

Delphix is designed for enterprise systems. It fits right into your current SAP security setup. All without requiring you to rebuild your security model or make big changes to how your SAP systems are set up. That’s because Delphix operates at the database layer, while SAP and other third party tools work at the application layer.

And SAP is probably not the only data you need to scramble and mask. You likely have other systems like Salesforce that need automated compliant data delivery. Delphix supports multiple integrations to help protect data across your entire tech stack. 

🎥 See how Delphix handles compliance and security across datasets like SAP and Salesforce in a short demo video.

This integrated solution creates custom scrambling rules for specific SAP data types. Thus, ensuring that specialized SAP structures are properly protected. It also provides detailed audit trails for compliance documentation. The result? It’s much easier for you to prove regulatory compliance during audits.

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