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Revolutionizing Data Validation

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Eliminated disruptive pipeline failures, ensuring seamless operations

Streamlined column validation development, boosting efficiency

Enhanced SLA adherence and increased customer satisfaction


Method Inc faced the critical challenge in validating XML content during their ELT process. Ensuring that XML data loaded into tables whilst maintaining requirements of strict formatting. Mismatches, even as minor as a single character, could disrupt the entire pipeline, resulting in costly failures.


Method Inc engineered an exceptional solution— creating a shared component which gathered information about the supplied table. Utilizing Python enabled methodical interaction of table structures, causing the creation of a versatile grid variable. Playing a pivotal role within a sophisticated calculator component, meticulously assessed the integrity of each and every column. 


  • Eliminated disruptive pipeline failures, achieving significant cost savings in terms of reprocessing and computing resources.
  • Enhanced SLA Adherence: The solution led to improved adherence to Service Level Agreements (SLAs), bolstering customer trust and satisfaction.
  • Streamlined the development, testing and deployment of column validation logic, making the entire process more efficient and effective.
  • Remarkable scalability- effortlessly handling the challenge of more than 100 columns populated via XML or JSON.