Optimising Data Migration with Parallel Job Execution
In the dynamic landscape of modern banking, data migration is a critical operation that demands precision, speed, and efficiency. Our recent collaboration with an esteemed bank underscores the pivotal role Allevio played in revolutionising their data migration process. Facing a substantial challenge in transferring customer records from a legacy system to a new platform, the bank turned to us to orchestrate a solution that would not only expedite the process but also ensure accuracy and resource optimisation.
The Challenge
The bank, a prominent player in the financial industry, grappled with a massive data migration project. With close to 7 million customer records dispersed across multiple tables, the task at hand was monumental. Although upload scripts were crafted in the form of SQL Procedures, they proved to be inefficient. A dry run using mock records underscored the urgency for a swifter and more effective solution. The extended duration of 21 hours for migration was deemed impractical, necessitating a paradigm shift.
Our Solution: Leveraging Java's Multithreading for Efficiency
Recognising the urgency of the situation, Allevio swiftly devised a solution to optimise the data migration process. Our team harnessed the robust multithreading capabilities of Java to execute parallel jobs in predefined batches of records. This intelligent approach optimised CPU utilisation, ensuring that peak loads of the CPU were efficiently leveraged for maximum efficiency.
Key Features of the Solution
Parallel Job Execution: By breaking down the migration process into parallel jobs, Allevio enhanced efficiency and significantly reduced migration time.
Predefined Batching: Strategic batching of records ensured a balanced distribution of workload, minimising resource bottlenecks.
Optimised CPU Utilisation: The algorithm intelligently harnessed the CPU's peak performance, avoiding resource wastage and enhancing overall throughput.
Rescuing Efficiency: From 21 Hours to 3.5 Hours
The impact of our solution was remarkable. The migration time that initially demanded an impractical 21 hours was slashed to a mere 3.5 hours. This colossal improvement of over 80% not only met the bank's expectations but also positioned them for enhanced operational efficiency and customer service excellence.
Our collaboration with the bank serves as a testament to Allevio's commitment to innovative problem-solving. By leveraging Java's multithreading capabilities and crafting a smart algorithm, we transcended the challenges of a colossal data migration project. The results speak for themselves – an exponential improvement in efficiency, substantial time savings, and an elevated capacity to adapt to the dynamic demands of modern banking. At Allevio, we stand at the forefront of transformation, turning challenges into success stories that redefine industry benchmarks.