Sync Order Files from Google drive to Datalake
$0.00
| Workflow Name: |
Order and Product File Sync to Datalake -Using Google Drive |
|---|---|
| Purpose: |
Automatically extract order and product files from Google Drive and load them into the Datalake. |
| Benefit: |
Ensures centralized; up-to-date order and product data for analytics; reporting; and downstream workflows. |
| Who Uses It: |
Data Engineers; Operations Teams; Analytics Teams |
| System Type: |
File-Based Integration Workflow |
| On-Premise Supported: |
Yes (via secure proxy if needed) |
| Supported Protocols: |
HTTPS; REST API |
| Industry: |
E-commerce; Retail; Wholesale & Distribution; Manufacturing; Technology Services |
| Outcome: |
Centralized, up-to-date order and product data available in the Datalake |
Table of Contents
Description
| Problem Before: |
File processing was manual; slow; and error-prone; causing delays in data availability. |
|---|---|
| Solution Overview: |
Automated Google Drive file read; parsing; transformation; and secure Datalake ingestion. |
| Key Features: |
Google Drive connector; file versioning; CSV/Excel parsing; schema validation; batch logging. |
| Business Impact: |
Improves data consistency; reduces manual overhead; and speeds up reporting cycles. |
| Productivity Gain: |
Removes file download/upload work and manual parsing efforts. |
| Cost Savings: |
Cuts file processing overhead by up to 60%. |
| Security & Compliance: |
OAuth tokens encrypted; Google Drive security respected |
File Sync Integration – Order and Product Files to Datalake Using Google Drive
File Sync Integration automates the extraction of order and product files from Google Drive and loads them directly into the Datalake. This workflow ensures centralized, consistent, and up-to-date file-based datasets for analytics and reporting.
Centralized & Up-to-Date File Ingestion for Analytics
The workflow retrieves files from Google Drive, validates their structure, and prepares them for downstream use in the Datalake. Teams benefit from simplified file management, improved data accuracy, and efficient support for analytics, operations, and reporting processes.
Watch Demo
| Video Title: |
Integrate NetSuite data to any Datalake |
|---|---|
| Duration: |
5:31 |
Outcome & Benefits
| Time Savings: |
Removes hours of weekly manual file processing |
|---|---|
| Cost Reduction: |
Reduces operational labor and file-handling overhead |
| Accuracy: |
Higher accuracy due to automated parsing and validation |
| Productivity: |
Enables 5× faster ingestion cycles |
Industry & Function
| Function: |
Data Extraction; File Sync; ETL Automation |
|---|---|
| System Type: |
File-Based Integration Workflow |
| Industry: |
E-commerce; Retail; Wholesale & Distribution; Manufacturing; Technology Services |
Functional Details
| Use Case Type: |
Order & Product Data Sync |
|---|---|
| Source Object: |
CSV/Excel order & product files |
| Target Object: |
Datalake tables for analytics |
| Scheduling: |
Hourly or near real-time |
| Primary Users: |
Data Engineering; Ops; BI Teams |
| KPI Improved: |
Data freshness; sync reliability; reporting speed |
| AI/ML Step: |
Optional anomaly detection on product updates |
| Scalability Tier: |
Mid-Enterprise |
Technical Details
| Source Type: |
Google Drive |
|---|---|
| Source Name: |
Order & Product File Folder |
| API Endpoint URL: |
https://www.googleapis.com/drive/v3/files |
| HTTP Method: |
GET |
| Auth Type: |
OAuth 2.0 |
| Rate Limit: |
~100 requests per 100 seconds per user |
| Pagination: |
Page token-based pagination |
| Schema/Objects: |
Orders; Products; Pricing; Metadata |
| Transformation Ops: |
File parsing; type conversion; deduplication; field mapping |
| Error Handling: |
Retry logic; file corruption detection; exception logging |
| Orchestration Trigger: |
Scheduled hourly or event-based |
| Batch Size: |
1-50 files per run |
| Parallelism: |
Parallel file downloads and parsing |
| Target Type: |
Cloud Datalake |
| Target Name: |
Order_Product_Datalake_Zone |
| Target Method: |
API Upload / Cloud Storage Write |
| Ack Handling: |
Logs for successful/failed file loads |
| Throughput: |
Up to 5;000 records/min depending on file size |
| Latency: |
<15 seconds per file |
| Logging/Monitoring: |
File-level logs; Google API logs; retry logs |
Connectivity & Deployment
| On-Premise Supported: |
Yes (via secure proxy if needed) |
|---|---|
| Supported Protocols: |
HTTPS; REST API |
| Cloud Support: |
AWS; Azure; GCP Datalakes |
| Security & Compliance: |
OAuth tokens encrypted; Google Drive security respected |
FAQ
1. What is the Order and Product File Sync to Datalake workflow?
It is an automated workflow that extracts order and product files stored in Google Drive and loads them into the Datalake for analytics, reporting, and downstream processing.
2. How does the workflow extract files from Google Drive?
The workflow connects to Google Drive using secure access, identifies the required files or folders, downloads the order and product files, processes them, and inserts the data into the Datalake automatically.
3. What file formats are supported?
The workflow can process common file formats such as CSV, Excel, JSON, and other structured data files stored in Google Drive.
4. How frequently can the workflow run?
It can be scheduled to run hourly, daily, weekly, or based on custom triggers depending on business needs and file update frequency.
5. What happens if no new files are available in Google Drive?
If no new or updated files are detected, the workflow completes successfully, logs the run, and ensures no unnecessary processing occurs.
6. Who uses this workflow?
Data Engineers, Operations Teams, and Analytics Teams use this workflow to maintain centralized and up-to-date order and product data in the Datalake.
7. What are the benefits of automating Google Drive file sync?
Automation ensures timely ingestion of order and product data, reduces manual file handling, supports consistent reporting, and enables smooth downstream analytics workflows.
Resources
Case Study
| Customer Name: |
Internal Operations / Data Engineering Team |
|---|---|
| Problem: |
Manual downloading and processing of order/product files from Google Drive caused delays |
| Solution: |
Automated workflow to sync order and product files from Google Drive to the Datalake |
| ROI: |
File availability improved 2-3× faster with reduced manual effort |
| Industry: |
E-commerce; Retail; Wholesale & Distribution; Manufacturing; Technology Services |
| Outcome: |
Centralized, up-to-date order and product data available in the Datalake |
