#data migration testing

Ensuring data accuracy in BI reports is critical for making the right business decisions. The iceDQ Qlik Testing Tool helps organizations validate and certify their Qlik Sense dashboards by automating data testing processes. Instead of relying on slow and inconsistent manual testing, iceDQ enables teams to perform scalable and efficient validation across apps, sheets, and visualizations.

With seamless integration into Qlik Sense environments, iceDQ allows users to embed dashboards, select specific visualizations, and apply real-time filters or bookmarks to replicate user scenarios. This ensures that the data displayed matches the underlying source systems accurately.

The platform also supports data reconciliation by comparing application data with databases, warehouses, or files, helping identify mismatches and errors at both row and aggregate levels. Additionally, users can create custom validation rules to enforce business logic, check KPIs, and maintain consistency in formats and calculations.

Migrating from SAP ECC to SAP S/4HANA involves complex data and process transformations. iceDQ’s SAP HANA migration testing solution helps validate this transition by comparing data between systems and ensuring accuracy. It performs end-to-end validation, including testing integrations and verifying data quality. The tool also supports incremental load validation and ensures referential integrity between datasets. With automated testing and detailed comparisons, it helps organizations reduce errors and achieve a reliable migration outcome with confidence.

Looking for a reliable Power BI report testing tool? iceDQ helps automate validation across reports, dashboards, and semantic models to ensure data accuracy and consistency. It enables businesses to test KPIs, visual elements, and datasets before deployment, reducing risks caused by incorrect insights. With support for DAX queries and automated checks, it simplifies testing workflows and improves reporting reliability. This solution ensures your Power BI reports are always aligned with underlying data and business rules, helping teams make confident, data-driven decisions.

Get an in-depth understanding of big data testing with a complete guide covering strategy, tools, and automation techniques. This resource explains how to validate complex data pipelines, including ETL workflows, data migration, and large-scale processing in distributed systems. It outlines essential testing approaches such as functional testing, performance testing, and data validation to ensure accuracy and consistency.

In this episode, host Chrystina sits down with Priyabrata Nandi, Vice President of Software Engineering at Fidelity Investments, to explore how enterprises can build AI systems that truly adapt to changing markets and why data reliability must be the foundation.

The immense digital growth witnessed over the last decade has moved digitization beyond being a mere business option anymore. It has become the driving force that allows organizations to sustain and succeed in this highly competitive world. Companies are constantly upgrading their legacy systems to cope with the ever-changing and evolving customer expectations. The upgrade often involves migrating the workflow process from an outdated system to a new one. Though migration might sound easy to achieve, migrating without losing any data is quite challenging. With advancement in technology, data has proven to become one of the most valuable assets of any organization. Data provides the right insights that help organizations make better decisions with a fact-based, data-driven approach. Hence, losing data while migrating to new systems can adversely affect the company; this is the key reason why data migration testing becomes vital.

Data migration testing is a verification process to ensure successful data migration to new systems with minimal disruption and data loss while maintaining data integrity. It also helps in ensuring that all the functional and non-functional objectives of the transition are achieved post-migration. However, not all data migration testing is effective enough to ensure all the goals are achieved. Following the best practices and strategies are essential as well as using appropriate data migration testing tools is important to make the migration successful. These best practices will help companies get the desired results from the tests.

Best Practices and Strategies for successful Data Migration Testing

Data migration errors can lead to adverse business and compliance risks that can make any company easily vulnerable to cybersecurity attacks. A thorough data migration testing can minimize the chances of errors and make the new systems more resilient. Here are the best practices to follow while performing data migration testing:

Multidisciplinary team approach