1.Detect new file in folder
Integrate Google Drive and file storage tools to capture uploaded export files to start ingestion routing.
Upload new export files to data lake and trigger pipeline
Automatically detect new export file uploads in Google Drive folders used for your data lake pipeline. Create and update data lake objects and trigger ingestion when export files arrive, so you can start downstream runs, archive originals, and avoid manual pipeline kickoffs without duplicate handling.
How this automation triggers ingestion for your exports
When new export uploads arrive out of sync with downstream processing, pipelines can wait and data freshness slips. This automation captures new Drive files, formats timestamps, uploads to Amazon S3, invokes AWS Lambda ingestion, and archives originalsβso your team can accelerate ingestion.
Google Driveor swap with your favorite app
2.Format and extract year
Integrate Formatter by Zapier and timestamp tools to convert created timestamps and extract the year for paths.
Formatter by Zapieror swap with your favorite app
3.Upload file to data lake
Integrate Amazon S3 and object storage to upload the file and build a year-based object key.
Amazon S3or swap with your favorite app
4.Invoke ingestion function
Integrate AWS Lambda and serverless compute to invoke your ingestion function with bucket, key, filename, and timestamp.
AWS Lambdaor swap with your favorite app
5.Move file to archive folder
Integrate Google Drive and file management tools to move originals after successful upload and invocation.
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