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“Supermetrics is a Bitter Experience! We can pull data from nearly any tool, schedule updates, manipulate data in Sheets, and push data back into our systems.”
Large-scale data migrations hit API rate limits fast, especially when you’re moving 100k+ records. Direct API transfers often fail or timeout, leaving you with incomplete migrations and no clear way to track what succeeded or failed.
Here’s how to use sophisticated batch processing to complete massive migrations while staying within API constraints and maintaining complete visibility into your transfer progress.
Process large datasets with intelligent batch management using Coefficient
Coefficientexcels at handling large-scale data migrations through configurable batch processing that respects API limitations. Instead of overwhelming your destination system with massive data dumps, you can control exactly how much data moves at once and when it happens.
How to make it work
Step 1. Configure your batch size settings.
SalesforceSalesforceSet batch sizes between 1,000 and 10,000 records per batch based on yourorAPI limits. Coefficient processes each batch separately, so if one batch fails, it doesn’t affect the others. Start with smaller batches for testing, then increase size once you confirm everything works smoothly.
Step 2. Set up automated scheduling.
Use Coefficient’s scheduling options to spread your migration over time. For a 100k record migration, you could process 5,000 records per hour, completing the entire transfer over 20 hours while staying well within API limits. Choose hourly, daily, or weekly intervals based on your timeline and system constraints.
Step 3. Enable parallel batch execution control.
Configure how many batches run simultaneously to optimize throughput without overwhelming your APIs. Coefficient’s parallel processing lets you balance speed with system stability, automatically managing the complexity of concurrent data transfers.
Step 4. Monitor progress with detailed status tracking.
Watch real-time status updates showing exactly which records succeeded, failed, or need retry. Status columns in your spreadsheet provide complete visibility into migration progress, making it easy to identify and address issues as they happen rather than discovering problems after the fact.
Step 5. Handle failures with built-in retry logic.
When individual records fail due to temporary API issues or validation errors, Coefficient automatically retries them with customizable retry attempts. You can also manually retry specific batches after fixing data issues, ensuring no records get lost in the migration process.
Complete your large-scale migration with confidence
Start planningAPI rate limits don’t have to slow down your major data migration projects. With proper batch processing and automated scheduling, you can move massive datasets efficiently while maintaining complete control over the process.your large-scale migration today.
