Coordinate SAP ETL Testing with DataLark

Ensure seamless data integration and transformation across your SAP landscape with DataLark's advanced ETL testing capabilities. Validate, automate, and optimize SAP data workflows, reducing errors and accelerating time-to-value.

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1. Connect Systems
2. Define Test Datasets & Scenarios
3. Execute Automated Data Validation
4. Monitor & Manage
5. Generate Reports

DataLark seamlessly integrates with both SAP ECC and SAP S/4HANA environments, leveraging its native connectors to communicate with core SAP objects. Extract relevant business objects while preserving referential integrity between related data (e.g., Materials, BOMs, Documents). Whether you're working with financial data, material management, sales orders, or customer records, DataLark ensures secure and efficient connections across your SAP landscape.

Use the no-code, drag-and-drop interface to select specific objects and conditions (e.g., customers from a certain region, materials created in the last 90 days). This ensures test datasets are relevant, lightweight, and consistent. Utilize DataLark's visual test designer to create comprehensive ETL validation scenarios. Define source-to-target mappings, set up data quality rules, and configure business logic validations.

Run automated ETL tests that validate 100% of your data transformations. DataLark compares source SAP data against target systems, validates business rules, checks data completeness, and identifies transformation errors. By eliminating manual interventions, this step speeds up the testing process and reduces human errors. Execute tests in parallel for faster validation of large datasets.

Monitor test execution in real-time with detailed progress tracking and performance metrics. DataLark provides comprehensive test reports showing pass/fail status, data quality scores, and detailed error analysis. Set up automated alerts for test failures and quality threshold breaches.

Access detailed test documentation in PDF, CSV, or Excel formats for audit and compliance purposes. DataLark maintains complete test history, data lineage tracking, and validation logs to support regulatory requirements and change management processes.

We've earned the trust of global enterprises

SAP ETL Testing Challenges Addressed by DataLark

S/4HANA Migration Validation

Manufacturing

Use Case:

A global manufacturing company migrating 15 years of SAP ECC data to S/4HANA needs comprehensive validation of material master, BOM, and financial data transformations.

Leverage DataLark to:

Validate Universal Journal transformations from classic GL
Test material master data model changes (MARA/MARC consolidation)
Verify BOM structure integrity and component allocations
Ensure production version and routing data accuracy

Financial Data Consolidation Testing

Financial Services

Use Case:

A multi-national bank consolidating regional SAP systems requires validation of complex financial data transformations for regulatory reporting and risk management.

Leverage DataLark to:

Test chart of accounts mapping and consolidation rules
Validate currency conversion and exchange rate applications
Verify cost center and profit center hierarchy transformations
Ensure compliance with IFRS and local GAAP requirements

Master Data Harmonization Validation

Pharmaceuticals

Use Case:

A pharmaceutical company post-merger needs to validate harmonization of customer, vendor, and material master data across acquired SAP systems.

Leverage DataLark to:

Test duplicate detection and merge algorithms
Validate address standardization and geocoding
Verify customer hierarchy and classification mappings
Ensure regulatory compliance data integrity

Supply Chain Integration Testing

Retail

Use Case:

A global retailer integrating SAP with external e-commerce and logistics platforms requires validation of real-time inventory and order data synchronization.

Leverage DataLark to:

Test bi-directional inventory synchronization accuracy
Validate order-to-cash process data flows
Verify pricing and promotion data consistency
Ensure real-time stock level accuracy across channels

Data Warehouse ETL Testing

Healthcare

Use Case:

A healthcare organization validating SAP patient billing and clinical data transformations for analytics and reporting data warehouse.

Leverage DataLark to:

Test patient data de-identification and masking
Validate clinical coding and classification mappings
Verify insurance claim processing accuracy
Ensure compliance in data transformations

Cloud Migration Validation

Technology

Use Case:

A technology company migrating on-premise SAP to SAP S/4HANA Cloud requires comprehensive validation of data transformations and API integrations.

Leverage DataLark to:

Test OData API data synchronization accuracy
Validate cloud-specific data model transformations
Verify integration with cloud-native applications
Ensure security and access control data integrity

Regulatory Reporting Validation

Energy & Utilities

Use Case:

A utilities company needs to validate SAP IS-U data transformations for regulatory reporting and smart meter data integration.

Leverage DataLark to:

Test meter reading data validation and cleansing
Validate billing calculation accuracy and adjustments
Verify customer classification and tariff applications
Ensure compliance with utility regulatory requirements

Key Benefits

Comprehensive Data Handling

DataLark goes beyond simple data extraction and loading. It enables complex transformations, data validation, and cleansing as part of your SAP ETL testing workflow. Whether you're validating the transformation of financial records or ensuring the consistency of master data, DataLark supports a variety of use cases, including test data generation, masking, and cross-system validation.

No-Code Test Design for Business Users

DataLark empowers SAP functional consultants and business analysts to create comprehensive test scenarios without coding. DataLark's visual interface allows domain experts to define business rules, validation logic, and quality checks using drag-and-drop components and pre-built SAP validation templates.

Seamless SAP Integration

With built-in connectors for SAP ECC and S/4HANA, DataLark ensures tight integration with your SAP ecosystem. The platform handles communication with both SAP standard and custom business objects, ensuring the accuracy and reliability of extracted data. DataLark also supports key SAP integration technologies such as RFC and BAPI to ensure smooth and secure data extraction.

Enterprise-Scale Performance & Security

With DataLark, you can process millions of SAP records with parallel execution and optimized performance. DataLark supports enterprise security requirements including SNC, SSO, role-based access controls, and encryption at rest and in transit. Deploy on-premise, in cloud, or hybrid environments to meet your security and compliance needs.

Robust Monitoring Tools

DataLark's monitoring and reporting capabilities provide transparency at every step of the testing lifecycle. Customizable logs and reports give you visibility into the performance of data provisioning, transformation, and validation processes. Automated alerts ensure you’re immediately informed of any issues, allowing for quick action and minimizing testing delays.

Trusted by Leaders in the Industry

A leading global automotive manufacturer
A global leader in industrial automation
A global manufacturer of architectural products

Problem

The client faced challenges validating complex SAP S/4HANA migration involving 25 million material master records, 500,000 BOMs, and 10 years of financial transactions across 12 countries. Manual validation was impossible, and existing tools couldn't handle SAP-specific business logic.

Solution

DataLark provided comprehensive ETL testing automation for the S/4HANA migration. Key validation scenarios included:

Material Master Transformation: Validating MARA/MARC table consolidation and new field mappings.
BOM Structure Validation: Ensuring component allocations and routing integrity.
Financial Data Migration: Testing Universal Journal transformations and currency conversions.
Organizational Structure: Validating plant, company code, and controlling area mappings.
Custom Object Migration: Testing custom fields, user exits, and enhancement implementations.

The solution delivered automated validation across all migration phases with real-time monitoring and comprehensive reporting.

Results

The client achieved successful S/4HANA migration with zero data integrity issues and full audit compliance.

95%

Reduction in Manual Testing Effort: Automated validation eliminated weeks of manual verification work.

99.8%

Data Accuracy Achievement: Comprehensive validation ensured near-perfect data quality in the target system.

60%

Faster Migration Timeline: Parallel testing and automated validation accelerated overall project delivery.

Problem

The client faced challenges in maintaining high-quality master data across their SAP landscape. The complexity of their operations, involving numerous SAP objects such as materials, BOMs, and others, led to:

Data inconsistencies across various SAP modules, affecting reporting and decision-making.
Manual validation efforts, requiring extensive time and resources to ensure compliance with business rules.
Error propagation due to lack of proactive data quality checks, impacting downstream processes like procurement, production planning, and finance.
Difficulty in maintaining data integrity as multiple systems contributed to data creation and updates.

These challenges resulted in inefficiencies, operational risks, and increased costs associated with poor data quality.

Solution

To address these issues, the client leveraged DataLark as a platform for data quality management. The solution introduced:

Automated Data Extraction: Seamlessly reading and analyzing master data from SAP, covering materials, BOMs, and other key objects.
Business Rule Validation: Configurable rule sets to automatically detect data inconsistencies, missing attributes, duplicate records, and misaligned relationships.
Deviation Reporting: Reports highlighting data quality issues, allowing stakeholders to take corrective action.
Automated Adjustments: For predefined scenarios, the system corrected data inconsistencies automatically, reducing manual intervention.
Continuous Monitoring: Ongoing validation to ensure data integrity as new records were created or modified.

This approach enabled the client to establish a proactive data governance framework, ensuring SAP master data met business and regulatory requirements.

Results

With DataLark, the client established a scalable and efficient data quality management process, ensuring that SAP master data remained accurate, reliable, and aligned with business objectives.

65%

Reduction in Manual Reconciliation Efforts: Automated validation streamlined data comparison, significantly reducing the need for manual intervention.

50%

Improvement in Data Consistency: Intelligent rule-based validation minimized discrepancies and enhanced data reliability.

40%

Faster Issue Resolution: Automated deviation reports and alerts enabled quicker identification and correction of data mismatches.

Problem

The client had issues with ensuring data consistency between multiple systems, including SAP and external databases. Some of the challenges were:

Complex data validation requirements, involving multilevel comparisons across different data sources.
Manual reconciliation efforts, which were time-consuming and prone to errors.
Lack of a standardized framework for defining and managing data validation rules, leading to inconsistencies.
Dependence on IT for developing alternative solutions making it difficult for data management teams to adapt validation logic to evolving needs.

These issues resulted in delays in data processing, inaccurate reporting, and inefficiencies in operations that relied on synchronized master data.

Solution

To overcome these challenges, the client implemented DataLark as a data validation platform. Key features included:

Automated Data Extraction: Seamlessly reading data from multiple sources, including SAP and external databases.
Flexible Data Mapping: Providing an intuitive interface for business users to define relationships between datasets without technical expertise.
Configurable Multilevel Validation Rules: Enabling comparison logic across different hierarchies, including product structures, pricing conditions, and supplier information.
User-Friendly Rule Management: Allowing master data teams to create, modify, and manage validation rules without IT involvement.
Deviation Reports and Alerts: Automatically identifying discrepancies and presenting them in easily understandable reports.

With DataLark, the client eliminated the need for custom development, enabling business users to maintain and adapt validation rules independently.

Results

With DataLark, the client established a scalable, efficient, and user-friendly approach to data validation, ensuring data accuracy across critical business processes.

70%

Reduction in Manual Reconciliation Efforts: Automated validation replaced labor-intensive data comparison, freeing up resources for higher-value tasks.

90%

Improvement in Data Accuracy: Faster identification and resolution of discrepancies ensured more reliable and consistent data.

50%

Increase in Business Agility: Master data teams could modify validation rules independently, reducing reliance on IT and accelerating response times.

Explore Opportunities for Automated SAP ETL Testing

Talk to Our Experts

FAQ

What is SAP ETL Testing?

SAP ETL (Extract, Transform, Load) testing involves validating the entire data flow process from the source system to SAP environments (like SAP ECC or SAP S/4HANA). This includes testing the extraction of data, the transformation rules applied to it, and ensuring it is correctly loaded into the target SAP system. The goal is to ensure that the data remains accurate, consistent, and complete throughout the ETL process.
What SAP systems does DataLark support for ETL testing?

DataLark supports comprehensive ETL testing for SAP ECC 6.0+, SAP S/4HANA (on-premise and private cloud), SAP BW/4HANA, and SAP industry solutions. Our native connectors work with all major SAP modules including FI/CO, SD, MM, PP, QM, and custom developments.
How does DataLark help with SAP migration testing?

DataLark plays a critical role in SAP migration projects by ensuring data integrity and quality during the migration from legacy SAP systems (like SAP ECC) to newer platforms (like SAP S/4HANA). DataLark automates the extraction, transformation, and validation of data, ensuring that the migration is successful and data is correctly mapped and transformed according to the new system’s requirements.
Can DataLark validate complex SAP business logic during ETL processes?

Yes. DataLark understands SAP business objects, organizational structures, and configuration dependencies. The platform can validate complex scenarios like material determination, pricing procedures, account determination, and workflow configurations during data transformations.
Does DataLark support automated regression testing for SAP changes?

Absolutely. DataLark maintains baseline test results and automatically detects deviations in subsequent test runs. This enables comprehensive regression testing for SAP transports, configuration changes, and system updates.
Can DataLark validate data transformations across heterogeneous systems?

Yes. DataLark validates data flows between SAP and non-SAP systems including databases, cloud platforms, APIs, and file systems. Our platform handles format conversions, data type mappings, and business rule validations across diverse technology stacks.
How does DataLark ensure security during SAP ETL testing?

DataLark implements enterprise-grade security including SAP SNC encryption, SSO integration, role-based access controls, and audit logging. All data access follows SAP authorization concepts and maintains complete security compliance.
What kind of reports does DataLark generate for ETL testing?

DataLark provides comprehensive test reports including data quality scores, validation results, error analysis, and performance metrics. Reports are available in PDF, Excel, and CSV formats with customizable templates for different stakeholders.
Can DataLark integrate with existing DevOps and testing frameworks?

Yes. DataLark supports integration with CI/CD pipelines, test management tools, and automated deployment frameworks. Our platform can be triggered via APIs, scheduled execution, or event-driven workflows to fit your existing development processes.

Coordinate SAP ETL Testing with DataLark

How It Works

S/4HANA Migration Validation

Financial Data Consolidation Testing

Master Data Harmonization Validation

Supply Chain Integration Testing

Data Warehouse ETL Testing

Cloud Migration Validation

Regulatory Reporting Validation

Trusted by Leaders in the Industry

Problem

Solution

95%

99.8%

60%

Problem

Solution

65%

50%

40%

Problem

Solution

70%

90%

50%

Explore Opportunities for Automated SAP ETL Testing

FAQ