Production is going on.
More Than 26 Billion Records Migrated with Automated Validation
BCT combined Python automation, coordinated vendor delivery and global business testing to complete a large-scale cloud data migration and improve reporting reliability.
Client
Challenge
The migration involved billions of records supporting business reporting across products, customers, invoices and orders. Repeated regression testing at this scale required substantial time and rigour across data layers. Upstream hard deletes and backdated source entries also created data inconsistencies that complicated validation.
Delivery depended on coordination across multiple vendors, each working with interconnected data and migration requirements. Changes to legacy systems continued into the final phase, expanding the scope from 12 to 195 VTABs and increasing the dependencies the team needed to manage.
The organisation needed to complete the migration with reliable data for downstream reporting while accommodating these changes. Business acceptance also required coordinated testing across regions, with more than 200 users participating simultaneously.
Delivery depended on coordination across multiple vendors, each working with interconnected data and migration requirements. Changes to legacy systems continued into the final phase, expanding the scope from 12 to 195 VTABs and increasing the dependencies the team needed to manage.
The organisation needed to complete the migration with reliable data for downstream reporting while accommodating these changes. Business acceptance also required coordinated testing across regions, with more than 200 users participating simultaneously.
Solution
BCT introduced Python-based data validation to automate a major testing bottleneck. The scripts supported 18 regression cycles over three months, with each cycle validating millions of records across 26 tables. Automation reduced manual effort and the time required for regression testing and user acceptance testing.
To align delivery across vendors, BCT established a POD-based approach focused on critical tables and columns. This gave teams a shared basis for reviewing scope and resolving discrepancies across data layers, helping them manage dependencies and progress delivery.
The migration used Snowflake and Coalesce alongside the Oracle product data warehouse environment. BCT continuously validated migration dependencies and used agile change-request handling to accommodate the expanding scope. Six additional shadow resources were used at peak during the final phase, with timeline extensions managed as part of the delivery approach.
BCT coordinated UAT with business representatives across the US, EMEA, Australia and Asia. Working with client IT leadership, the team identified key business participants and orchestrated concurrent testing to support phased go-live execution.
To align delivery across vendors, BCT established a POD-based approach focused on critical tables and columns. This gave teams a shared basis for reviewing scope and resolving discrepancies across data layers, helping them manage dependencies and progress delivery.
The migration used Snowflake and Coalesce alongside the Oracle product data warehouse environment. BCT continuously validated migration dependencies and used agile change-request handling to accommodate the expanding scope. Six additional shadow resources were used at peak during the final phase, with timeline extensions managed as part of the delivery approach.
BCT coordinated UAT with business representatives across the US, EMEA, Australia and Asia. Working with client IT leadership, the team identified key business participants and orchestrated concurrent testing to support phased go-live execution.
Impact
The programme successfully migrated and validated more than 26 billion records across 26 tables, covering critical business data and master data management. The migration improved operational efficiency and the reliability of downstream reporting, including Tableau, after go-live.
Automated validation enabled the team to sustain repeated testing at scale with less manual effort. The shared approach to critical tables and columns reduced cross-vendor discrepancies, while disciplined scope and dependency management helped the programme absorb significant changes through its final phase.
More than 200 business users participated in coordinated global UAT, supporting business alignment and phased deployment. The completed programme established a cloud data foundation for enterprise reporting, with client feedback recognising BCT’s support across regions throughout the migration.
Automated validation enabled the team to sustain repeated testing at scale with less manual effort. The shared approach to critical tables and columns reduced cross-vendor discrepancies, while disciplined scope and dependency management helped the programme absorb significant changes through its final phase.
More than 200 business users participated in coordinated global UAT, supporting business alignment and phased deployment. The completed programme established a cloud data foundation for enterprise reporting, with client feedback recognising BCT’s support across regions throughout the migration.
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Bahwan CyberTek is committed to providing the highest level of protection regarding the processing of their vendors’/clients’/customers’/job applicants’/website visitors’ personal data based on applicable data protection laws and regulations at respective locations. In general, you can visit the Bahwan CyberTek website without providing personal data. However, there are times when Bahwan CyberTek will request personal data.
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