Harmonize Your SAP Data Replication with DataLark
Easily configure and automate SAP data delivery to a variety of destinations — including cloud platforms, on-prem systems, and hybrid storage.
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How It Works
- 1. Connect Systems
- 2. Configure Replication Flows
- 3. Transform & Validate Data
- 4. Automate Execution
- 5. Monitor & Control
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- Underground equipment manufacturer
- medical device company
- Semiconductor equipment manufacturer
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The client relied on an outdated mass maintenance tool to handle key data management tasks, including price condition updates, material creation, and BOMs, documents, and routings maintenance.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 Automated SAP Data Replication
FAQ
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What SAP systems does DataLark support for replication?
DataLark supports both SAP ECC and SAP S/4HANA environments, seamlessly integrating with core SAP modules such as MM (Materials Management), SD (Sales and Distribution), FI/CO (Financial Accounting and Controlling), PLM (Product Lifecycle Management), as well as other modules. It uses standard protocols like RFC, BAPI, and HTTP/OData for reliable data integration and smooth communication across systems.
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Can I use DataLark to combine SAP data with data from other systems?Absolutely. DataLark supports multi-source pipelines, allowing you to integrate SAP data alongside inputs from databases, APIs, cloud apps, and file systems — all within the same workflow.
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Can DataLark load SAP data into cloud warehouses like Snowflake or BigQuery?Yes. DataLark supports popular cloud data warehouses including Snowflake, BigQuery, Redshift, and Azure Synapse. You can easily set SAP as a source and route data into your preferred analytics platform.
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Does DataLark support real-time data replication, or just batch?Both are supported. DataLark enables real-time replication via change data capture (CDC) where available, as well as scheduled batch jobs for historical loads or periodic updates.
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Does DataLark support incremental data extraction from SAP?Yes. Where available, DataLark leverages delta mechanisms (e.g., timestamps, change pointers) to support incremental loads. This reduces data transfer volume and improves performance for recurring jobs.
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Can I use DataLark to replicate multiple SAP objects in SAP?Yes. DataLark allows you to replicate multiple SAP objects in batch by using existing ones as templates. Instead of manually copying each object one by one, you can configure DataLark to use a reference object and generate multiple new objects based on it — adjusting key parameters where needed. This is especially useful when you need to create multiple Materials, BOMs, or DIRs with similar structures.
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How secure is SAP data replication with DataLark?Security is built into every layer of the platform. DataLark uses encrypted connections, supports role-based access controls, integrates with identity providers (e.g., SSO, SAML), and logs all activity for compliance auditing.