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Streamline SAP Data Upload with DataLark

Speed up your SAP data entry workflows with secure, no-code automation from DataLark.

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5

How It Works

  • 1. Connect & Import
  • 2. Map Data
  • 3. Validate and Standardize Data
  • 4. Automate Data Uploads
  • 5. Review Logs & Reports

1

Connect & Import
Use DataLark’s native connectors to integrate with your SAP (ECC, S/4HANA) system, import data from an Excel file or connect to the source system, either SAP or non-SAP (e.g., staging areas like MSSQL or Oracle databases).

2

Map Data
Visually map data across multiple formats and destinations using DataLark’s drag-and-drop interface. DataLark helps detect potential mapping issues by highlighting misalignments and providing guidance to support accurate configuration — enabling smoother data flow between systems.

3

Validate and Standardize Data
Use DataLark’s no-code transformation rule editor to resolve data quality issues by correcting invalid values, standardizing formats (e.g., units, codes, naming), and removing duplicates. For advanced or edge case scenarios, the platform also supports custom Python scripting to handle complex business rules or logic.

4

Automate Data Uploads
Automate recurring data transfers based on schedules or event-driven triggers, such as API calls, webhooks, or system events. DataLark can also send an email notification once a data transfer is completed, ensuring full visibility into your data workflows.

5

Review Logs & Reports
Keep full oversight of your data with detailed execution logs for successful data transfers and clear feedback when a run fails. Assess reports in multiple formats — including Excel, CSV, and others — as part of your monitoring process.

1

Connect & Import
Use DataLark’s native connectors to integrate with your SAP (ECC, S/4HANA) system, import data from an Excel file or connect to the source system, either SAP or non-SAP (e.g., staging areas like MSSQL or Oracle databases).

2

Map Data
Visually map data across multiple formats and destinations using DataLark’s drag-and-drop interface. DataLark helps detect potential mapping issues by highlighting misalignments and providing guidance to support accurate configuration — enabling smoother data flow between systems.

3

Validate and Standardize Data
Use DataLark’s no-code transformation rule editor to resolve data quality issues by correcting invalid values, standardizing formats (e.g., units, codes, naming), and removing duplicates. For advanced or edge case scenarios, the platform also supports custom Python scripting to handle complex business rules or logic.

4

Automate Data Uploads
Automate recurring data transfers based on schedules or event-driven triggers, such as API calls, webhooks, or system events. DataLark can also send an email notification once a data transfer is completed, ensuring full visibility into your data workflows.

5

Review Logs & Reports
Keep full oversight of your data with detailed execution logs for successful data transfers and clear feedback when a run fails. Assess reports in multiple formats — including Excel, CSV, and others — as part of your monitoring process.
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Streamline Mass Data Upload in SAP with DataLark
Request a Demo
Key Benefits
Increased Speed
Upload thousands of records in a fraction of the time compared to manual tools or scripts. Parallel streams can be enabled for faster throughput. Automate recurring data transfers and focus on strategic initiatives.
Enhanced Usability
Enable business users to upload data directly into SAP with a visual, no-code interface — without relying on custom development or IT support. Easily map standard and custom SAP fields and transactions.
Seamless SAP Integration
Connect with SAP ECC and S/4HANA using built-in connectors that support RFC, BAPI, and OData for reliable and smooth communication.
Versatility
Ensure data quality with live validation, optional test runs that simulate uploads without saving to SAP, and track changes for compliance. Save time, reduce risks, and ensure data integrity for enhanced decision making at the same time.
Clarity & Transparency
Gain full visibility into every data transfer with detailed logs. Generate clear, customizable Excel and CSV reports and share them instantly with relevant teams for quick remediation and audit tracking.

Trusted by Leaders in the Industry

  • 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 Mass Data Upload Automation

Talk to Our Experts

FAQ

  • Does DataLark replace LSMW or Migration Cockpit?

    DataLark is a modern, no-code alternative to LSMW and a flexible companion to SAP Migration Cockpit. Unlike LSMW, it provides a visual interface for mapping, transforming, and validating data — with no custom scripting required.

    For S/4HANA, DataLark helps prepare data in the formats required by Migration Cockpit: either by generating XML templates or loading directly into staging tables. This allows you to handle complex logic and transformation rules before the final SAP upload — speeding up migration and reducing errors.

    In cases where Migration Cockpit doesn’t support certain scenarios (e.g., historical data loads or custom objects), DataLark can connect directly to S/4HANA via BAPI or RFC — enabling broader coverage across business and technical use cases.

  • How does DataLark integrate with SAP?
    DataLark connects to SAP systems using standard communication methods such as BAPI, RFC, and OData. It supports both read and write operations, providing secure, near real-time access to your master and transactional data without custom development.
  • Does DataLark support non-SAP systems?
    Yes! In addition to SAP ECC and S/4HANA, DataLark supports a wide range of non-SAP systems — including databases, cloud platforms, enterprise applications, flat files, machine data, and message queues.
  • Can I upload custom fields or work with custom SAP objects?
    Absolutely. DataLark supports uploading to custom fields and objects as long as the required BAPIs or function modules are available and include those fields. If needed, your SAP team can extend standard interfaces, and DataLark will adapt — making it easy to map and load data without any scripting or backend changes in the application itself.
  • What happens if some records fail during upload?
    Failed records are clearly flagged with error messages. You can correct and re-upload only the failed entries — no need to start over. A detailed upload report is provided after every operation.
  • Is the upload process auditable and secure?
    Yes. DataLark uses secure, enterprise-grade integration with SAP. It connects through SAP JCo (Java Connector) and supports SAP SNC (Secure Network Communication) for encrypted authentication when properly configured. Additionally, DataLark enforces role-based access control to manage user permissions and maintains execution logs to support traceability and internal oversight.
  • What deployment options are available?
    DataLark offers flexible deployment options — on-premise (laptops, VDIs, Windows servers), in the cloud (SAP BTP, AWS, Microsoft Azure), or hybrid — to meet your organization’s technical and security requirements.
  • How long does it take to implement DataLark?
    Implementation time primarily depends on your landscape and internal onboarding policies for new applications. Most teams are up and running with DataLark within a few days to a few weeks — including infrastructure setup, SAP prerequisites (such as creating a dedicated user role for external access or importing transports, if required), installation, and guided onboarding.