Data lakes have become the preferred storage for unstructured data in enterprises, offering the flexibility to accommodate diverse data formats. However, the rise of unstructured data in data lakes brings with it new challenges in data quality and integrity. To mitigate the risk presented with these challenges, Narwal and Tricentis have joined forces, creating a robust, automated solution for managing unstructured data in the data lake ecosystem. 

Strategic Assurance for Complex Data Pipelines 

In an enterprise setting, data is more than just a resource; it’s a critical asset. Narwal and Tricentis offer a strategic approach to data quality through a comprehensive business assurance framework, tackling the complex needs of unstructured data quality in four essential areas: 

1. Business Process Assurance: Ensuring that data remains accurate as it flows through different processes, maintaining alignment with business objectives. 

2. Customer Experience Assurance: Validating customer-facing data, ensuring that data accuracy enhances user interactions and experience. 

3. Technology Assurance: Assessing the resilience of data as it passes through various technology layers. 

4. Data Integrity Assurance: Focusing on end-to-end validation to maintain data consistency from source to target, ensuring reliable information. 

Real-World Success: Automating Data Quality for Unstructured Sources 

For enterprises managing unstructured data, Tricentis Data Integrity has proven invaluable in automating data quality assurance. Narwal’s implementation of Data Integrity for both mainframe and XML file validation showcases the powerful impact of automation in streamlining data validation processes. 

1. Mainframe Data Validation: Unstructured mainframe files often don’t integrate well with modern data platforms. Data Integrity automated this validation, transforming a previously labor-intensive task into a seamless, reliable daily process. This solution allowed Narwal to validate large data volumes quickly, ensuring accuracy and saving valuable time and resources. 

2. XML Data Validation: With over 400 XML variations to validate, manual testing would have been unmanageable. Data Integrity automated every stage, from ingestion to final validation, allowing Narwal to meet rigorous data quality standards without the need for repetitive manual checks. 

Achieving Business Outcomes Through Automated Data Quality 

In today’s high-speed, data-centric world, organizations need data they can rely on. Data Integrity allows businesses to: 

1. Increase Coverage: Automated testing covers up to 90% of data, minimizing the risk of errors and reducing potential business disruptions. 

2. Reduce QA Cycles: Data Integrity cuts the QA cycle by 75%, enabling faster time-to-market and greater agility. 

3. Boost Business Confidence: Quality data underpins confident decision-making, which in turn, maximizes the ROI on digital initiatives. 

Narwal’s success in automating unstructured data validation demonstrates the strength of a clear, focused data strategy powered by intelligent automation. By partnering with Tricentis, Narwal has helped businesses overcome the inherent complexities of unstructured data, ensuring that decision-makers have access to accurate, trustworthy information when they need it most. 

For organizations navigating similar challenges, the Narwal-Tricentis partnership offers a compelling solution. With automated tools to handle diverse data types and formats, enterprises can achieve reliable business assurance, paving the way for confident, data-driven decisions that drive long-term success. 

If you’re ready to turn unstructured data complexity into a competitive advantage, join us for an exclusive webinar presented by Narwal in collaboration with Tricentis. We’ll go beyond the theory and into real use cases, showing how automation is helping enterprises prevent BI reporting failures, reduce risk, and boost confidence in every decision. This is your opportunity to learn directly from the teams transforming how data assurance is done. 

Save your seat for the webinar – Automating Data Quality: How to Prevent Costly BI Reporting Errors 
Date: May 7, 2025 | Time: 11:15 AM – 12:30 PM EST