Cable television giant accelerates and de-risks workload transformation using automation
Enhances productivity by automating the transformation of complex Netezza procedures to a cloud-compatible big data platform
Challenge
A leading US-based cable television company was looking to reduce their data storage and processing costs by transforming Netezza workloads to a cloud-compatible big data platform.
They wanted to:
- Get an advanced blueprint of the target architecture through a data-driven workload assessment
- Convert Netezza procedures into Hive compatible scripts
- Migrate relevant schema and datasets
- Verify transformed procedures
- Ensure data integrity and quality
- Leverage their existing investments in line with business goals
- Ensure business continuity and risk-free migration
Solution
LeapLogic, an Impetus product for automated workload transformation transformed the client’s data and procedures from Netezza to equivalent target compatible scripts on a cloud-compatible big data platform.
Leveraging a repeatable, verifiable methodology, LeapLogic automated schema and data migration, data migration quality checks, SQL scripts and procedures transformation, and code optimization to comply with their production SLAs.
Some Highlights:
- Provided schema optimization recommendations for partitioning, clustering, and number of buckets based on the dataset
- Migrated the existing dataset onto Hive
- Successfully automated and achieved 88% logic transformation of Netezza procedures into Hive compatible scripts
- Executed transformed procedures in the Hive environment
- Auto validated the transformed procedures against Netezza results
Impact
LeapLogic enabled the cable television company to enhance programmer and quality analyst productivity by automatically transforming 88% of queries into equivalent HiveQL. Our intelligent automation technique helped the client achieve:
- Risk-free migration with zero business disruption
- 50% cost and effort savings compared to manual migration
- Reuse of existing investments
- Faster time-to-market
- Informed data-driven decision making
- Data integrity through validation and quality checks
- Optimized performance in the target environment
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