58 lines
1.7 KiB
Markdown
58 lines
1.7 KiB
Markdown
# 📅 Day 1 — Setup and Data Ingestion
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## 🎯 Goal
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Establish the foundation for the project.
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The primary objective is to create an **n8n workflow** that successfully fetches raw **sales** and **product review data** from their respective sources.
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----
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## 🧩 Tasks
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### 1. Environment Setup
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- Set up your **n8n instance**:
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- Options: n8n Cloud, Docker, or local installation.
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- Reference: [https://docs.n8n.io/hosting/](https://docs.n8n.io/hosting/)
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- Create a **Python environment**.
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- Install necessary libraries:
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```bash
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pip install pandas nltk
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```
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---
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### 2. Create a New n8n Workflow
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- Start with a **Manual Trigger** node (`Start`).
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- This will later be replaced with an automated schedule on **Day 5**.
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---
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### 3. Fetch Sales Data
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- Add an **HTTP Request** or **Database Node (PostgreSQL/MySQL)**.
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- Connect to your e-commerce API endpoint (e.g., Shopify → `/orders.json`).
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- Set up credentials (API Key, OAuth2, etc.).
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- Test and verify that recent order data (e.g., order_id, product_id, price, quantity) is fetched successfully.
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---
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### 4. Fetch Product Reviews
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- Add another **HTTP Request** node.
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- Configure it to pull recent **product reviews** (e.g., review_text, rating).
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- Test independently to ensure successful data retrieval.
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---
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### 5. Combine Data Streams
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- Add a **Merge Node**.
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- Connect both sales and review nodes.
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- Set **Mode** → `Combine`.
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- This ensures both data sets are merged and available for the next phase.
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---
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## ✅ Deliverable
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A manually triggered **n8n workflow** that:
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- Pulls raw data from **two sources** (sales + reviews).
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- Combines them using a **Merge node**.
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- Outputs unified JSON data ready for analysis.
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