MH Alshaya delivers 99.99% Data Quality in Data Migration with DvSum


MH Alshaya, a franchisee Retailer based in Kuwait with 6B in revenue and operating over 4000 stores globally under 90 different brands, embarked on a comprehensive makeover of its information systems to establish a solid foundation for ongoing digital transformation. The resulting IT landscape includes Oracle, IBM, and Blue Yonder (JDA) as critical solutions deployed across a mix of on-premise, SaaS, and IaaS/PaaS platforms.

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The company had yet to have any systematic data quality process in place before. As they modernized their data landscape and implemented best-of-breed solutions, there was a clear recognition and need to

  1. Do a one-time cleansing and enrichment of data to improve data quality and make it fit for purpose to new systems and processes and
  2. Establish a systematic data quality process to maintain that high data quality.

The company evaluated tools from prominent box vendors and concluded that those were complex, cumbersome, and took a long time to set up, deploy, and difficult to use. The most significant gap was the ability to model complex business rules and orchestrate a process where business users could self-service cleanse the data as part of the data modernization program.


To address the challenge of ensuring high data quality during migration, Alshaya chose DvSum as their data quality solution provider. DvSum’s powerful business rules modeling capability, friendly user interface, and unique ability to provide master data cleansing and enrichment for business users made it the ideal choice for the company. Additionally, DvSum’s flexibility in setting up a dedicated instance in a specific global region to meet Alshaya’s data residency requirement was a critical factor in their decision.

With DvSum, Alshaya established a streamlined process for data cleansing and enrichment before migration, resulting in 99.99% of data migrated successfully and consistently. This process also reduced the time for data cleansing by five business days and resulted in significant user productivity savings. Overall, DvSum’s solution allowed Alshaya to achieve data migration quality assurance and accurately implement data migration quality checks for high-volume data migration.


As a result of using DvSum, MH Alshaya was able to streamline the process of data quality migration by ensuring that their data was accurate, reliable, and fit for purpose before migrating to new systems. The company achieved a 99.99% data migration success rate through using DvSum’s powerful business rules modeling capabilities and master data cleansing and enrichment interface designed for business. The streamlined process also reduced the time for data migration quality checks by five business days, resulting in significant savings in terms of user productivity.

Not only did DvSum help MH Alshaya achieve its goal of migrating high-quality data, but it also provided additional benefits, such as improved data quality at the time of data creation and the ability to manage data quality in a standardized, repeatable, and scalable fashion. The company achieved higher ROI from its investment in DvSum by expanding its use to other business units.


MH Alshaya's experience with DvSum's data quality solution highlights the importance of choosing the right data migration quality assurance tool. The company's initial struggles with complex and cumbersome solutions were alleviated when they switched to DvSum, which offered a powerful yet user-friendly solution for data quality migration. With DvSum, MH Alshaya was able to streamline its data migration process and achieve significant savings in terms of time and productivity while also achieving higher data quality across the organization. Overall, MH Alshaya's use of DvSum's data quality solution allowed them to achieve their goal of migrating high-quality data while providing additional benefits in terms of data quality management.

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Unlock the full potential of your data with DvSum

  • Create a unified view of your entire data landscape on Day 1
  • Streamline data governance with automatic data classification and enrichment
  • Improve data accuracy with integrated data quality and cleansing
  • Empower business users to get data insights with no-code self-service data exploration