Imagine preparing to move more than twenty years of business-critical data into a new cloud environment only to realize much of that data has never been systematically evaluated for its quality. That was the challenge facing a technology-forward quick-service restaurant chain as it embarked on a major on-prem-to-cloud migration. The organization planned to migrate data from its on-premises systems and recreate critical data products in a centralized cloud-based repository. But before the migration could deliver its promised value, the team needed confidence that the data could be trusted.
Picture This
Big Challenge
Twenty years of undetected data issues had caused several challenges:
Misaligned data and broken logic was caused by trying to force incompatible data together across three generations of ERP systems.
Failed join conditions introduced incorrect or dummy data.
Test data was captured as though it were real business data, creating a false impression of historical performance.
The biggest challenge was determining which historical records still provided actual business value, ensuring the new system wouldn’t be weighed down by unusable legacy data.
The Solution
To intentionally preserve historical data, Elder Research, a MANTECH company, guided and implemented key architectural decisions in the development of new Extract, Load, Transform (ELT) pipelines. The team extracted all relevant raw source data from the on-premises data warehouses and loaded it into the data lake, enabling progressive filtering of poor-quality records from historical extracts through detailed analysis.
Elder Research technical business analysts collaborated with the client’s engineering team to implement data tests at every stage of the pipeline, translating business-level assertions into executable tests to prevent bad data from being etched in stone.
To protect the system going forward, our Technical Business Analysts leveraged Anomalo to automatically flag anomalies in new incoming data, and Databricks Delta Lake integration to efficiently assess the downstream impact of code changes at scale.
The Results
Elder Research transformed the client’s on-premises data from an indiscriminate archive to a trusted source of insight, improving data reliability, protecting historical value, and supporting future growth.
Spotting the Real Issues:
We partnered with the client to identify the real data quality issues in their legacy environment and ensure new architecture decisions aligned directly with strategic goals. Rather than hoarding decades-old bad data, the technical business analysts were able to work closely with stakeholders to determine what historical data truly provided business value and filter out the rest.
Clinching the Execution:
Building on those insights, Elder Research implemented a series of modern ELT pipelines designed for flexibility and longevity. The architecture incorporated multiple layers of fail-safes, automated data quality checks, and comprehensive documentation to support ongoing maintenance and future enhancement. The result was a robust, scalable system that preserves valuable historical data while optimizing operational efficiency.
Bringing Everyone Along:
To ensure lasting success, we supported the client’s teams throughout migration and adoption of the new data products. Our analysts worked closely with the client’s change management team and led users through User Acceptance Testing sessions, empowering them to use the new data products confidently.