Data Delivery Method
After data scraping is completed, how to receive and use the data? The following are several common delivery methods, each suitable for different people and scenarios. The following table helps you quickly understand:
1. Delivery Method Comparison
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| Delivery Method | Suitable Users | Data Volume Range | Delivery Speed | Pros and Cons |
|---|---|---|---|---|
| Excel/CSV | Users familiar with Excel | Below 300,000 | Fastest | Simple and easy to use, but not suitable for complex or large data |
| JSON | Users with basic programming skills | Below 1 million | Fastest | Flexible and universal, but requires programming to process |
| Database (e.g., MySQL) | Users with strong programming skills | Above 1 million | Slower | Suitable for big data queries, deployment is slightly complex |
| Backend Management System | Users without programming background, need visualization | Unlimited | Slowest | Convenient to operate, but high development cost |
2. Excel/CSV Delivery
Suitable for: Users familiar with Excel, want to quickly analyze small to medium-scale data (such as product prices, user reviews).
Features:
- Data is delivered in table format (such as Excel or CSV files), easy to open and analyze.
- Example: After scraping e-commerce website product data, generate Excel tables showing prices and sales volume.
Figure: Excel table showing scraped Baidu search result data
Required Skills
- Basic Excel operations: filtering, sorting, formula calculations.
- Advanced features: pivot tables, chart displays.
Disadvantages
- When data volume exceeds 1 million, Excel may lag or require file splitting.
- Single cell can store maximum 32,767 characters, not suitable for long articles.
- Not suitable for complex data, such as structures where one product corresponds to multiple reviews.
Cost Reference: Usually no additional cost, included in development fees.
3. JSON Delivery
Suitable for: Users with basic programming skills, handling small to medium-scale data.
Features:
- JSON is a universal data format, suitable for processing in multiple programming languages (such as Python, JavaScript).
- Example: After scraping website user reviews, deliver in JSON format, programmers can easily import into programs for analysis.
Figure: JSON format showing scraped Baidu search result data
Advantages
- Flexible, supports complex data structures.
- Suitable for projects with larger data volumes (below 1 million).
Disadvantages
Requires programming skills to parse and use data.
Cost Reference: Usually no additional cost, included in development fees.
4. Database Delivery (e.g., MySQL, PostgreSQL, MongoDB)
Suitable for: Users with strong programming skills, handling large-scale data (millions and above).
Features:
- Data is stored in professional databases, suitable for fast queries and analysis.
- Example: After scraping millions of product data from e-commerce platforms, store in MySQL, sorting by sales volume to get top 10 takes only a few seconds.
Figure: MySQL database showing product data
Advantages
- Suitable for large data volumes, fast query speed.
- Supports complex queries, such as sorting or filtering by multiple conditions.
Disadvantages
Requires database management knowledge, deployment and maintenance are complex.
Cost Reference: May require additional payment for server and database maintenance fees, approximately 500-1000 CNY/month.
5. Backend Management System Delivery
Suitable for: Users without programming background, need visual operations.
Features:
- Provides web system, like a "data dashboard", where you can directly view, search, and modify data.
- Example: After scraping product data, search by price or sales volume through the backend system, view chart analysis.
- Supports multi-user permissions (administrators can modify data, regular users can only view).
- Can generate line charts, bar charts and other visual reports with fast response speed.
Figure: Backend system showing data search and charts
Disadvantages
High development and maintenance costs, longer delivery time.
Cost Reference
Depending on function complexity and data volume, cost approximately 3000 to tens of thousands of CNY.
6. Other Delivery Methods
According to project requirements, you can also choose the following flexible methods:
File Download
After scraping data daily, organize into Excel, CSV or PDF, upload to server for users to download.
Figure: Interface for users to download Excel data
API Service
Provide data interfaces (API), users request data through programs; or we actively push data to user systems.
Figure: Schematic diagram of obtaining data through API
Cost Reference: File download and API services are usually free, but require additional server fees (approximately 100-300 CNY/month).
Summary and Recommendations
Choosing data delivery methods depends on your technical capabilities and project requirements:
Small-scale Projects (Below 300,000)
Excel/CSV is simplest, suitable for quick analysis.
Medium-scale Projects (Below 1 Million)
JSON is flexible, suitable for users with programming skills.
Large-scale Projects (Above 1 Million)
Database queries are efficient, suitable for professional teams.
No Technical Background
Backend management system is most user-friendly, but cost is higher.