Enhance SAP Data Quality Monitoring with DataLark

Monitor, analyze, and maintain SAP data quality in real-time — ensuring continuous data reliability, proactive issue detection, and automated quality governance across your data landscape.

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1. Connect Systems
2. Define Quality Metrics
3. Automate Continuous Monitoring
4. Review Alerts & Insights
5. Investigate & Resolve

Connect to SAP ECC, S/4HANA, and third-party systems using DataLark’s out-of-the-box connectors. Map data relationships, dependencies, and business-critical data flows to create a complete data quality monitoring foundation. Setup is fast, secure, and requires no coding or middleware. Whether your data lives in SAP tables or is distributed across cloud sources, DataLark brings it together into a unified monitoring layer without disrupting existing workflows.

Configure business-defined data quality rules using a powerful no-code rule engine. Choose from prebuilt templates for standard validations — completeness, accuracy, consistency, duplication, referential integrity — or create custom checks tailored to your unique governance model. Specify thresholds, dimensions, and conditional logic, ensuring that your rules align with real business requirements, not just technical constraints.

Schedule data quality checks to run hourly, daily, or at key milestones, such as data loads, approvals, or workflow completions. Rules execute against live SAP data, monitoring for issues like missing values, outdated records, or rule violations. DataLark can also respond to real-time events via change data capture (CDC) or API integrations, allowing for proactive detection rather than reactive cleanup.

Get instant notifications when data quality issues are detected. DataLark generates real-time alerts with clear descriptions of the issue, affected records, and suggested remediation steps. Prioritize issues by business criticality and automatically route alerts to the appropriate teams for rapid resolution.

Drill into flagged records to understand root causes and take corrective actions — all within the DataLark platform. Users can comment on, update, or enrich problematic records, and even trigger downstream processes like data cleansing or enrichment. Once resolved, the system revalidates the data and updates status dashboards automatically, ensuring a complete quality feedback loop.

We've earned the trust of global enterprises

SAP Data Quality Monitoring Challenges Addressed by DataLark

Master Data Quality Governance

Manufacturing

Use Case:

A global automotive manufacturer needs continuous monitoring of material master data quality across 50+ plants to ensure production planning accuracy and regulatory compliance.

Leverage DataLark to:

Monitor material master completeness and accuracy in real-time
Detect duplicate materials and inconsistent classifications
Validate engineering change management data integrity
Ensure supplier master data compliance with automotive standards

Financial Data Integrity Monitoring

Banking & Financial

Use Case:

An international bank requires continuous monitoring of financial data quality across multiple SAP systems to ensure regulatory compliance and accurate risk reporting.

Leverage DataLark to:

Monitor GL account postings for accuracy and completeness
Detect anomalies in transaction patterns and amounts
Validate customer master data for KYC compliance
Ensure real-time data quality for regulatory reporting

Customer Data Quality Assurance

Telecom

Use Case:

A telecom operator needs real-time monitoring of customer master data quality to support billing accuracy, service provisioning, and customer experience initiatives.

Leverage DataLark to:

Monitor customer master data completeness and accuracy
Detect billing address inconsistencies and service conflicts
Validate contract data integrity and pricing accuracy
Ensure data quality for customer analytics and personalization

Supply Chain Data Monitoring

Retail

Use Case:

A global retailer requires continuous monitoring of vendor and procurement data quality to optimize supply chain operations and ensure compliance with sourcing policies.

Leverage DataLark to:

Monitor vendor master data accuracy and completeness
Detect pricing inconsistencies and contract violations
Validate purchase order data integrity and approval workflows
Ensure supplier compliance data quality for ESG reporting

Healthcare Data Quality Compliance

Healthcare

Use Case:

A healthcare organization needs continuous monitoring of patient and clinical data quality to ensure HIPAA compliance, billing accuracy, and clinical decision support.

Leverage DataLark to:

Monitor patient master data accuracy and privacy compliance
Detect clinical coding errors and documentation gaps
Validate insurance and billing data integrity
Ensure data quality for clinical research and outcomes analysis

Production Data Quality Control

Manufacturing

Use Case:

A chemical manufacturer requires real-time monitoring of production and quality control data to ensure product safety, regulatory compliance, and operational efficiency.

Leverage DataLark to:

Monitor batch production data completeness and accuracy
Detect quality control measurement anomalies
Validate recipe and specification data integrity
Ensure traceability data quality for regulatory compliance

Asset Management Data Monitoring

Energy & Utilities

Use Case:

A utilities company needs continuous monitoring of asset and maintenance data quality to optimize asset performance, ensure safety compliance, and support predictive maintenance initiatives.

Leverage DataLark to:

Monitor equipment master data accuracy and completeness
Detect maintenance history inconsistencies and gaps
Validate work order data integrity and resource allocation
Ensure asset performance data quality for analytics and optimization

Key Benefits

Real-Time SAP Data Observability

Gain unprecedented visibility into your SAP data landscape with continuous monitoring and intelligent anomaly detection. DataLark tracks data quality metrics across all SAP modules in real-time, providing instant alerts when quality thresholds are breached. Our platform understands SAP business context and organizational structures to deliver meaningful quality insights.

Business-Friendly Monitoring

Create, edit, or manage monitoring rules without writing a single line of code. Business analysts and data stewards can configure complex quality logic using a drag-and-drop interface. This empowers domain experts to lead data governance initiatives without depending on IT for implementation, fostering agility and cross-team collaboration.

Integrated SAP & Enterprise Coverage

Get your data under control regardless of its source. Whether you're monitoring vendor master data in S/4HANA or reconciling financial entries across SAP and legacy systems, DataLark provides a centralized platform to monitor quality across your entire data landscape. This unified approach reduces silos, eliminates blind spots, and supports consistent quality practices across departments and systems.

Proactive Issue Resolution

Transform from reactive to proactive data quality management with intelligent alerting and automated remediation workflows. DataLark provides root cause analysis, impact assessment, and guided resolution steps to minimize data quality issues' business impact and accelerate problem resolution.

Clear Reporting & Accountability

Built-in dashboards, scorecards, and audit logs make it easy to demonstrate compliance, track progress, and share results with stakeholders. Assign data owners to each rule, monitor resolution SLAs, and build a culture of accountability around data integrity. Reports can be tailored by role, department, or business unit for maximum transparency.

Trusted by Leaders in the Industry

A leading global pharmaceutical company
A global leader in industrial automation
A global manufacturer of architectural products

Problem

The client struggled with data quality issues across their global SAP landscape affecting regulatory compliance, clinical trials, and manufacturing operations. Manual quality checks were insufficient for their complex, multi-country environment with strict FDA and EMA requirements.

Solution

DataLark implemented comprehensive data quality monitoring across the client's SAP environment. Key monitoring capabilities included:

Regulatory Compliance Monitoring: Real-time validation of batch records, quality control data, and traceability information
Master Data Quality Assurance: Continuous monitoring of material, vendor, and customer master data across all regions
Clinical Data Integrity: Automated validation of clinical trial data and adverse event reporting
Manufacturing Quality Control: Real-time monitoring of production data, specifications, and quality measurements
Supply Chain Compliance: Continuous validation of supplier qualifications and audit data

The solution provided 24/7 monitoring with intelligent alerting and automated compliance reporting.

Results

The client achieved significant improvements in data quality, regulatory compliance, and operational efficiency.

90%

Reduction in Data Quality Issues: Proactive monitoring and automated validation prevented quality problems before business impact.

75%

Faster Regulatory Reporting: Automated quality validation and compliance documentation accelerated regulatory submission processes.

85%

Improvement in Audit Readiness: Continuous monitoring and quality documentation ensured constant audit readiness and compliance.

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 Data Quality Monitoring

Talk to Our Experts

FAQ

How does DataLark monitor SAP data quality in real-time?

DataLark connects to SAP systems using native protocols (RFC, BAPI, OData) and continuously monitors data changes through SAP change documents and application logs. Our platform validates data quality rules in real-time and provides instant alerts when quality issues are detected.
Can DataLark monitor data quality across multiple SAP systems?

Yes. DataLark provides centralized monitoring across your entire SAP landscape including ECC, S/4HANA, BW, and industry solutions. Our platform correlates data quality metrics across systems and provides unified dashboards for enterprise-wide quality visibility.
What types of data quality rules can DataLark monitor?

DataLark supports various quality rules including completeness, accuracy, consistency, timeliness, validity, and business-specific validations. Our platform understands SAP organizational structures, master data hierarchies, and business process dependencies to provide contextual quality monitoring.
Can DataLark integrate with existing data governance frameworks?

Absolutely. DataLark integrates with enterprise data governance platforms, quality management systems, and compliance frameworks. Our platform provides APIs and standard connectors for seamless integration with existing governance workflows and reporting systems.
What kind of alerts and notifications does DataLark provide?

DataLark offers intelligent alerting with configurable severity levels, escalation procedures, and notification channels (email, SMS, API webhooks). Alerts include root cause analysis, business impact assessment, and recommended remediation actions for faster issue resolution.
Can DataLark monitor custom SAP developments and enhancements?

Yes. DataLark can monitor data quality for custom SAP tables, fields, and business logic. Our platform adapts to your specific SAP configuration and custom developments to provide comprehensive quality monitoring across your entire SAP environment.
Can this be used by business users, or is it only for IT teams?

DataLark is designed for both technical and business users. The intuitive interface allows business analysts, data stewards, and domain experts to monitor data quality without needing developer support.

Enhance SAP Data Quality Monitoring with DataLark

How It Works

Master Data Quality Governance

Financial Data Integrity Monitoring

Customer Data Quality Assurance

Supply Chain Data Monitoring

Healthcare Data Quality Compliance

Production Data Quality Control

Asset Management Data Monitoring

Trusted by Leaders in the Industry

Problem

Solution

90%

75%

85%

Problem

Solution

65%

50%

40%

Problem

Solution

70%

90%

50%

Explore Opportunities for Automated SAP Data Quality Monitoring

FAQ