Accelerate SAP Test Data Management with DataLark
Deliver secure, production-like test data for SAP environments faster and with greater confidence with DataLark.
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How It Works
- 1. Connect to SAP Systems
- 2. Define & Subset Test Data
- 3. Transform & Prepare Data
- 4. Automate Test Data Provisioning
- 5. Monitor & Manage
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Problem
The client’s existing data maintenance processes for SAP classification master data and allocations for DIR and materials were manual, inconsistent, and prone to errors.
Key challenges included:
- Difficulty managing large-scale updates to classification data.
- Limited visibility into data accuracy and versioning.
- High operational costs due to repetitive manual tasks.
These inefficiencies hindered the client’s ability to scale and maintain accurate, reliable data as their operations expanded.
Solution
DataLark enabled the client to automate the mass creation and ongoing updates of SAP classification master data and allocations. With intuitive tools for bulk processing and validation, the platform empowered business users to:
- Ensure consistency and accuracy in classification data.
- Reduce manual workload through automated workflows.
- Monitor and manage updates with robust reporting and analytics.
DataLark’s seamless integration with SAP ensured data integrity and streamlined ongoing maintenance tasks.
Results
The client now benefits from scalable and efficient data maintenance, enabling them to support growth and innovation.
75%
75% Reduction in manual effort for classification updates.
90%
90% improvement in data accuracy and reliability.
60%
60% faster processing of classification data changes.
Problem
The client relied on an outdated mass maintenance tool to handle key data management tasks, including price condition updates, material creation, and BOMs, documents, and routings maintenance. The legacy system presented several challenges:
- Limited functionality and lack of scalability for modern requirements.
- Frequent errors and inconsistencies in mass updates.
- High dependency on IT teams for data changes, causing delays in operations.
These inefficiencies led to slowed decision-making and increased operational costs, impacting the client's ability to remain agile in a competitive market.
Solution
DataLark replaced the legacy mass maintenance tool, providing a modern, user-friendly platform to streamline data management processes. Key improvements included:
- Automated mass updates for price conditions, materials, BOMs, documents, and routings.
- Simplified workflows enabling business users to perform data updates without IT intervention.
- Advanced validation and reporting to ensure accuracy and compliance with business rules.
With its seamless SAP integration and robust functionality, DataLark became the central hub for managing large-scale data changes efficiently.
Results
The client now operates with a modernized data maintenance process, driving greater agility and cost savings while supporting their strategic growth initiatives.
70%
70% reduction in processing time for mass data updates.
50%
50% decrease in data errors and inconsistencies.
55%
55% improvement in operational efficiency through reduced IT dependency.
Problem
The client managed mass updates using SAP’s standard LSMW (Legacy System Migration Workbench), which posed significant limitations for their growing business needs:
- Time-consuming and complex setup for mass updates.
- Limited flexibility to handle modern data maintenance scenarios.
- High risk of errors due to manual processes and lack of user-friendly validation tools.
- No centralized platform for mass creation, updates, or deletion of data such as MM, BOM, documents, and business partners.
These challenges resulted in inefficiencies, increased operational costs, and delays in critical data maintenance activities.
Solution
DataLark replaced the standard SAP LSMW, providing a modern and intuitive platform for handling mass data maintenance tasks. Key enhancements included:
- Streamlined workflows for mass creation, updates, and deletions across materials, BOMs, documents, and business partners.
- Built-in validation and error-checking mechanisms to ensure data accuracy.
- Simplified processes that empowered business users to perform data updates without technical expertise.
- Centralized management and reporting for improved visibility and traceability.
DataLark’s robust SAP integration eliminated the inefficiencies of manual LSMW processes while delivering scalability and flexibility.
Results
With DataLark, the client transformed their data maintenance processes, enabling rapid, accurate, and efficient data management to support their expanding operations.
85%
85% faster execution of mass data maintenance tasks.
90%
90% reduction in errors through automated validation and user-friendly tools.
65%
65% improvement in operational efficiency by enabling business users to handle data changes independently.
Explore Opportunities for Enhanced SAP Test Data Management
FAQ
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How does DataLark support SAP test data management?
SAP Test Data Management involves creating, managing, and provisioning high-quality, representative datasets to validate SAP applications. It ensures that development and QA teams have the right data to test functionality without relying on full production sets.
DataLark connects directly to SAP systems (ECC and S/4HANA) to extract relevant data subsets while preserving referential integrity. Users can transform, enrich, or adapt this data using no-code rules or low-code scripting — enabling the creation of realistic, purpose-built test datasets tailored to specific scenarios.
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Can DataLark help mask or anonymize sensitive SAP data?Yes. DataLark allows users to configure rule-based transformations to pseudonymize or modify sensitive fields — such as customer names or personal identifiers — using no-code rules or Python scripting. This helps reduce exposure of real data during testing and supports compliance goals.
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Can I simulate synthetic test data with DataLark?Yes. DataLark enables you to simulate synthetic data by customizing values through transformation rules or Python scripting — allowing you to create realistic test data without relying entirely on production inputs.
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What SAP modules are supported?DataLark works with SAP data across various modules including FI (Finance), MM (Materials Management), SD (Sales and Distribution), HCM (Human Capital Management), DMS (Document Management System), and more. It supports cross-functional test data workflows by extracting and managing data from relevant SAP tables and structures based on your configuration.
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Can I automate test data provisioning with DataLark?Yes. You can schedule recurring test data extractions, automate masking rules, and provision test data directly into target environments using DataLark’s orchestration tools, thus eliminating manual overhead and reducing wait times.
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Does DataLark require technical SAP expertise to use?Not at all. DataLark is designed with a no-code interface that enables business users, QA engineers, and data stewards to manage test data workflows independently. Technical teams can extend functionality further through advanced configuration and scripting options.
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Where can I deploy DataLark?DataLark can be deployed on-premise, in private or public cloud environments, or in a hybrid model — giving you the flexibility to meet security, compliance, and infrastructure requirements.
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Does DataLark support audit logging and access controls?Yes. DataLark includes robust access management features, including role-based permissions and detailed audit logs, ensuring that only authorized users can access or manipulate test data, and all actions are traceable for compliance.