Automation pipeline built with Google Apps Script to process, transform, and archive spreadsheet data across multiple Google Sheets.
This project demonstrates an early-stage structured approach to automating spreadsheet-based data workflows.
This project automates a workflow that processes records from multiple sheets, performs filtering and metric parsing, restructures the data, and archives the results.
The goal is to reduce manual spreadsheet work and ensure consistent data processing across different spreadsheets.
Manual processing across multiple spreadsheets leads to:
- repetitive data handling
- inconsistent transformation logic
- increasing effort as data volume grows
These issues make it difficult to maintain efficiency and consistency in collaborative workflows.
The workflow is structured as a sequential processing pipeline:
- filtering raw data from source sheets
- parsing metrics from structured text fields
- transforming data into a consistent format
- grouping and sorting records for analysis
- archiving processed results for traceability
This design enables a clear and repeatable data processing flow.
Source Sheets
│
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Data Filtering
│
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Metric Parsing
│
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Sorting & Grouping
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Output Table
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Data Transformation
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Archive & Backup
src/
├─ core/
├─ transform/
└─ archive/
docs/
├─ architecture.md
├─ workflow.md
└─ code-structure.md
- Google Apps Script
- JavaScript
- Google Sheets
This project is currently being refactored into a public demonstration version.
Sensitive data and internal workflow details have been removed before publication.
This project represents the initial stage of an evolving automation workflow:
-
Multi-Source Data Processing Automation
Introduces structured intermediate datasets and modular processing across multiple data sources -
Ticket Data Matching System with Incremental Processing
Further extends the workflow into a reusable data matching system with incremental processing
This project focuses on solving a concrete operational problem and serves as the starting point for later system design improvements.