If you want to succeed in the digital game, your core business data must be right and available everywhere it’s needed, fast.  Learn how Enterprise Data Insight can help you automate your data management and faster processes to transform your SAP Landscape and solve your business challenge

Internation HQ Contact Details
USA HQ

255 S Orange Avenue, Suite 104, Orlando, FL 32801, United States

+1.561.440.8060

EUROPE HQ

71-75 Shelton Street, Convent Garden, London, WC2H 9JQ, UK

+44.2045.770.664

Email and Support contact

info@edatainsight.com

support@edatainsight.com

Twitter Facebook-f Linkedin Youtube

Your Trusted Partner for SAP, Cloud & Data Strategy

We're here to help you make sense of your data and turn it into measurable business value. Whether you're exploring a project, need expert advice, or just want to learn more about our solutions — drop us a message. Let's create something impactful together.

Contact us
```
SAP Test Data Management

Dynamic Data Replicator business use case

Automate SAP refreshes, deliver test ready systems faster, and reduce manual effort and data risk across non production landscapes.

Start Readiness Assessment Book a DDR demo
  • Faster refresh delivery from request to test ready
  • Predictable outcomes with repeatable run books
  • Improved governance for non production data handling

Why SAP test data becomes a delivery bottleneck

Manual SAP refresh activities create delays, inconsistency, and avoidable risk. DDR standardises and automates the test data lifecycle.

Long refresh cycles
Weeks from request to usable system slows sprint delivery and testing.
High manual effort
Multiple handovers and rework increase Basis and functional workload.
Inconsistent data
Different targets end up with different outcomes, reducing test confidence.
Data governance risk
Sensitive data exposure in non production increases compliance pressure.

Before and after DDR

A simple comparison for executives, delivery leads, and SAP Basis.

Before DDR
Manual, slow, and hard to repeat
  • Manual SCCL and refresh run steps
  • Unpredictable timelines and long windows
  • Repeated remediation and configuration fixes
  • High reliance on individuals and tribal knowledge
  • Limited ability to refresh frequently
After DDR
Automated, predictable, and scalable
  • Standardised refresh execution and templates
  • Repeatable run books with predictable outcomes
  • Reduced manual handovers and rework
  • Consistent test data handling across targets
  • More frequent test ready refresh delivery

Business use case summary

DDR supports faster delivery, reduced operational overhead, stronger governance, and improved test confidence.

Objective
Reduce time from refresh request to test ready system and remove manual bottlenecks.
Outcome
More reliable test cycles and release timelines, with consistent environments.
Governance
Improved control and auditability for non production data operations.
Generate a board ready decision pack
Complete the readiness assessment to produce a tailored management summary and a DDR business use case PDF suitable for CIO and steering committee approval.
Generate my PDF Speak to an expert
Designed for SAP landscapes
Works across complex ECC and S/4HANA non production refresh needs.
Built for delivery velocity
Supports faster test cycles and improved release confidence.
Board friendly outputs
Turns readiness answers into a management ready approval document.
```

BLOCK 1: EDI Question Bank

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Ut elit tellus, luctus nec ullamcorper mattis, pulvinar dapibus leo.

Enterprise Data Insight
Customer Use Cases and Deployment Patterns for Dynamic Data Replicator
Document
Use case library
Version
V2
Date
Customer use cases

Your guide to customer journey to Dynamic Data Replicator

This library summarises common SAP data management challenges, how DDR resolves them, and the outcomes you can expect.
SAP test data management Targeted replication Delta refresh Data masking
Customer use cases for Dynamic Data Replicator

Executive summary

Dynamic Data Replicator enables fast, controlled replication of relevant SAP data into non production environments, improving delivery speed, testing quality, and operational resilience. It supports targeted replication, repeatable delta refreshes, and built in data masking to reduce risk and protect sensitive information. This document provides a set of practical use cases covering development, production support, training, sandbox environments, periodic refreshes, divestitures, maintenance downtime cover, and cost reduction in HANA landscapes.

Delivery outcome
Faster, repeatable data provisioning
Risk outcome
Reduced exposure of sensitive data
Operational outcome
Improved testing quality and continuity

Use cases

Use Case 01
Development
New development client for improved unit testing
Improve DEV unit testing with production like quality data.
Use Case 02
Support
Production support
Surgically copy production issues into non production for resolution.
Use Case 03
Training
Refreshing data in training clients
Keep training clients fresh with small, reusable datasets.
Use Case 04
Sandbox
New client in sandbox system
Align repository objects and create a quality sandbox baseline.
Use Case 05
Delta
Periodic delta refreshes
Automate repeatable refresh of changing master data objects.
Use Case 06
Security
In place data transformation
Scramble sensitive data in non production to meet compliance and reduce risk.
Use Case 07
Programme
Business divestitures
Extract only the required data for a divested SAP system.
Use Case 08
Continuity
Mitigating SAP maintenance downtime
Provide short term coverage for operational teams during downtime windows.
Use Case 09
Full copy
Removing the stale data issue from full production copies
Keep full copies relevant with regular refresh of current transactional information.
Use Case 10
HANA
Reducing the cost of HANA deployments
Create smaller fully functional clients to reduce HANA footprint and cost.

Use Case 01. New development client for improved unit testing

Problem
Application teams have low quality data in DEV, leading to poor unit testing or no unit testing. Changes are promoted to QA without adequate testing, increasing rework and transport volumes.
Solution
Create a unit test client in DEV using DDR best practice. Copy configuration and master data from production, then copy an appropriate slice of transactional data, such as one month. Add additional slices later as required.
Benefits
Restore DEV to its intended purpose and improve change quality. Reduce transports released, reduce lifecycle cost, improve development quality, and reduce production failures caused by insufficient testing.

Use Case 02. Production support

Problem
Teams should not perform production support activity in production. Recreating issues manually in non production is time consuming, costly, and often difficult.
Solution
DDR surgically copies the data objects at issue from production into a non production environment. Related transactional and master data is included to ensure consistency with production.
Benefits
Faster resolution without production risk. Reduced effort for application teams and improved production efficiency.

Use Case 03. Refreshing data in training clients

Problem
Training clients require frequent refresh, consuming resources and database space and increasing infrastructure cost. Alternatively, training teams create data manually, increasing time and cost.
Solution
Create a training specific client in the appropriate system using DDR. Copy configuration and master data from production, then copy only relevant transactional segments. Delete and reimport reusable datasets as often as required.
Benefits
Smaller footprint and lower infrastructure cost. Faster refresh cycles and reduced manual creation of training data.

Use Case 04. New client in sandbox system

Problem
Sandbox clients are often not part of the transport path. Over time the system falls out of sync and data becomes stale.
Solution
Use DDR Object Alignment to compare source and target and resolve repository deltas. Create a small high quality client, then copy only the required transactional data in a targeted manner.
Benefits
Improved sandbox quality and relevancy. Smaller client footprint with faster deletion and rebuild when needed.

Use Case 05. Periodic delta refreshes

Problem
Master data objects such as customers, vendors, and materials change frequently. Test environments require periodic refresh using an easy and repeatable approach.
Solution
Use DDR Intelligent Slice to define a date range across multiple objects. Use Export Control to schedule exports, then import manually or automatically. Move the date range forward using Adjust date range and schedule via standard SAP jobs.
Benefits
Consistently refreshed master data in one or more clients with minimal ongoing effort. Time savings and more relevant data for testing.

Use Case 06. In place data transformation

Problem
Non production systems may contain sensitive data following a copy. Regulations and internal audit requirements demand scrambling of certain data objects. There is also risk of accidental real world outputs from non production.
Solution
Use DDR to scramble sensitive data in place within the non production client. Maintain data transform rules in the target client, or copy them from a reference client. Export and import occur within the same system client to achieve transformation.
Benefits
Reduced exposure of sensitive information and reduced compliance risk. Real world like data becomes usable without unintended consequences.

Use Case 07. Business divestitures

Problem
A business entity is being divested and only specific master and transactional data must be copied to the new system.
Solution
Use DDR to extract only the required divested dataset and integrate it into the target system. Due to complexity and varying scope, partner with EDI to define the optimal approach and sequencing.
Benefits
Copy only the data required for the divested environment. Accelerate divestiture timelines where time is critical.

Use Case 08. Mitigating SAP maintenance downtime

Problem
SAP systems require downtime for maintenance. Businesses operating across time zones expect availability at all times, including weekends.
Solution
Use DDR to spin up a small fully functional client with a subset of data in a short timeframe. Operational teams use it during downtime to view work activities, customer details, and technical information, then confirm and close work when production returns.
Benefits
Reduced impact of downtime and improved continuity for mission critical activities. A more productive workforce and improved customer service.

Use Case 09. Removing the stale data issue from full production copies

Problem
Some organisations require full production copies for compliance or regression. Full copies take time, require post copy reconfiguration, and transactional data becomes stale quickly.
Solution
Create the full copy using standard SAP procedures, then use DDR to regularly refresh it with the most up to date transactional information. Use the refreshed full copy as a source for DEV, QA, and training environments.
Benefits
Continual supply of relevant transactional data. Reduced need for full refresh cycles, reducing effort and cost.

Use Case 10. Reducing the cost of HANA deployments

Problem
HANA performance gains come with higher infrastructure cost. Non production environments often multiply overall HANA footprint significantly.
Solution
Use DDR to create smaller fully functional clients for DEV, training, and QA. Reduce the required HANA landscape footprint while maintaining quality and usability.
Benefits
Reduced hardware footprint and cost, with rapid return on investment. Ongoing benefits from faster builds, quality data, and reduced delivery risk.

Deployment patterns

Deployment recommendation
DDR can be deployed flexibly across different environments including Solution Manager, different clients, production systems, or cloud. A common pattern is to use a pre production system as a source for non production environments to support delta copying and reduce load on production.
Benefits
Efficient data synchronisation, reduced refresh effort, improved production performance, and a cohesive data ecosystem where non production systems remain aligned.
Complex landscape integration
Central console deployment in Solution Manager or dedicated client environments can provide the adaptability required for complex landscapes. As landscapes grow, DDR supports swift configuration additions for additional systems.
Isolated production system
For high profile landscapes requiring isolation, DDR supports secure transfer through file export and import. This approach accommodates environments where direct connectivity is restricted.

Support information

EDI provides support by telephone or email for DDR issues and processes. If offices are closed or staff are temporarily unavailable, responses are provided within 24 hours of the initial inquiry. Export and import issues may require enhancements and resolution time depends on complexity. Updates and fixes are deployed to customers with active maintenance, and customers decide if and when to implement updates. Planning sessions can be scheduled to review changes and assess feasibility for specific projects.

Want a customer specific version of this document
Provide your current challenge and landscape facts, and we will generate a board ready use case pack aligned to your scope and governance.
Speak to EDI
Use Case 01
New development client for improved unit testing
Improve DEV unit testing with production like quality data.
Want a customer specific board pack. Share your challenges and we will map the best DDR approach and scope.
Request a demo